2012 Electronic Imaging - SPIE · 2011. 10. 26. · 22–26 January 2012 Hyatt Regency San Francisco Airport Hotel Burlingame, California, USA electronicimaging.org Advance Technical

Conference Dates22–26 January 2012

Hyatt Regency San Francisco Airport Hotel

Burlingame, California, USA

electronicimaging.org

Advance Technical Program

2012ElectronicImaging

Register Today

22–26 January 2012

Technologies

- Multimedia, Mobile Devices, and Web 2.0

- Computer Vision

- Algorithms and Systems

- Digital Imaging Sensors and Applications

- Image Processing and Quality

- Visualization and Human Perception

- 3D Imaging, Interaction, and Measurement

2 electronicimaging.org • TEL:+17036429090 • [email protected]

The cutting edge of imaging research

Come explore the state of the art in imaging technologies as the world’s leading researchers from industry and academia share their latest findings in 3D imaging, imaging systems, and multimedia and visual image processing.

- 20 conferences with more than 800 presentations

- Plenary presentations from leading experts

- Demonstration session and 3D Theatre

- Interactive Paper Session

- All-Conference Reception

ElectronicImaging

IS&T/SPIE

22–26 January 2012

Advance Technical Program

22–26 January 2012 | Hyatt Regency San Francisco Airport Hotel, Burlingame, California, USA

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electronicimaging.org • TEL:+17036429090 • [email protected] 3

ContentsOrganizing Committees . . . . . . . . . . . . . . . . . . . . . . . . . . .4SpecialEvents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5Plenary Presentations. . . . . . . . . . . . . . . . . . . . . . . . . . . . .6Conference Daily Schedule . . . . . . . . . . . . . . . . . . . . . . . .7

Conferences 3D Imaging, Interaction, and Measurement . . . . . . . . . 8-18Imaging, Visualization, and Perception . . . . . . . . . . . 19-31Image Processing. . . . . . . . . . . . . . . . . . . . . . . . . . . . 32-38Digital Image Sensors and Applications . . . . . . . . . . 39-46Multimedia Processing and Applications . . . . . . . . . . 47-54Visual Information Processing and

Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . 55-56

CoursesCourse Daily Schedule . . . . . . . . . . . . . . . . . . . . . . . . 58-593D Imaging, Interaction, and Measurement . . . . . . . . . . .60Digital Image Sensors and Applications. . . . . . . . . . . . . .62Image Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67Imaging, Visualization, and Perception . . . . . . . . . . . . . .73Multimedia Processing and Applications . . . . . . . . . . . . .78Visual Information Processing and

Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82

Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84-85Proceedings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86

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Technical Organizing Committee

Sos S. Again, The Univ. of Texas at San Antonio (United States)

David Akopian, The Univ. of Texas at San Antonio (United States)

Adnan M. Alattar, Digimarc Corp. (United States)

Jan P. Allebach, Purdue Univ. (United States)

Atilla M. Baskurt,Univ.ofLyon(France)

Sebastiano Battiato, Univ. degli Studi di Catania (Italy)

Philip R. Bingham, Oak Ridge NationalLab.(UnitedStates)

Charles A. Bouman, Purdue Univ. (United States)

Peter D. Burns, Consultant (United States)

David P. Casasent, Carnegie Mellon Univ. (United States)

Chaomei Chen, Drexel Univ. (United States)

Reiner Creutzburg, Fachhochschule Brandenburg (Germany)

Huib de Ridder, Technische Univ. Delft (Netherlands)

Edward J. Delp, Purdue Univ. (United States)

Jeffrey M. DiCarlo, Intuitive Surgical, Inc. (United States)

Tiarna Doherty, J. Paul Getty Museum (United Kingdom)

Margaret Dolinsky, Indiana Univ. (United States)

Antoine Dupret, École Supérieure d’IngénieursenElectroniqueetElectrotechnique(France)

Karen O. Egiazarian, Tampere Univ. of Technology (Finland)

Reiner Eschbach, Xerox Corp. (United States)

Zhigang Fan, Xerox Corp. (United States)

Gregg E. Favalora, Optics for Hire (United States)

Frans Gaykema, Océ Technologies B.V. (Netherlands)

Atanas P. Gotchev, Tampere Univ. of Technology (Finland)

Onur G. Guleryuz, DoCoMo CommunicationsLabs.USA,Inc.(United States)

Ming C. Hao, Hewlett-Packard Labs.(UnitedStates)

Nicolas S. Holliman, Durham Univ. (United Kingdom)

Francisco H Imai, Canon Development Americas Inc. (United States)

David L. Kao, NASA Ames Research Ctr. (United States)

Lyndon Kennedy, Yahoo! Research (United States)

Edmund Y. Lam, The Univ. of Hong Kong (China)

Qian Lin, Hewlett-PackardLabs.(United States)

Gabriel G. Marcu, Apple Inc. (United States)

Ian E. McDowall,FakespaceLabs,Inc. (United States)

Nasir D. Memon, Polytechnic Institute of NYU (United States)

Valérie Nguyen, CEALetiMINATEC(France)

Thrasyvoulos N. Pappas, Northwestern Univ. (United States)

Ilya Pollak, Purdue Univ. (United States)

John Recker, Hewlett-Packard Labs.(UnitedStates)

Alessandro Rizzi, Univ. degli Studi di Milano (Italy)

Brian Rodricks, Fairchild Imaging (United States)

Bernice E. Rogowitz, Visual Perspectives Consulting (United States)

Juha Röning, Univ. of Oulu (Finland)Amir Said, Hewlett-PackardLabs.

(United States)Nitin Sampat, Rochester Institute of

Technology (United States)Nicu Sebe, Univ. degli Studi di

Trento (Italy)Robert Sitnik, Warsaw Univ. of

Technology (Poland)Cees G. M. Snoek, Univ. van

Amsterdam (Netherlands)Robert L. Stevenson, Univ. of Notre

Dame (United States)David M. Stone, Univ. of Delaware

(United States)Christian Viard-Gaudin, Univ. of

Nantes (France)Guijin Wang, Tsinghua Univ. (China) Ralf Widenhorn, Portland State

Univ. (United States)Patrick J. Wolfe, Harvard Univ.

(United States)Pak C. Wong, Pacific Northwest NationalLab.(UnitedStates)

Andrew J. Woods, Curtin Univ. (Australia)

Feng Xiao, Fairchild Imaging (United States)

Richard Zanibbi, Rochester Institute of Technology (United States)

Symposium Cochair

Gaurav SharmaUniversity of Rochester

Symposium Chair

Majid RabbaniEastmanKodakCompany

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ElectronicImaging

IS&T/SPIE

Symposium Steering Committee:

Majid Rabbani, SymposiumChair,EastmanKodakCo.

Gaurav Sharma, Symposium Co-chair, Univ. of Rochester

Sabine Süsstrunk, Past Symposium Chair, École PolytechniqueFédéraledeLausanne

Geoff Wolfe, Course Chair, Canon Information Systems ResearchAustraliaPty.Ltd.

Choon-Woo Kim, Course Cochair, Inha Univ.

Nitin Sampat, Technical Advisory Chair, Rochester Institute of Technology

Ron Scotti, SPIEScienceandTechnologyAdvisor

Suzanne E. Grinnan, IS&TExecutiveDirector

Rob Whitner, SPIEEventManager

Conference Dates22–26 January 2012

Hyatt Regency San Francisco Airport Hotel,

Burlingame, California, USA


Special Events

Onsite Registration HoursSunday22January..................10:00amto4:00pmMonday23January....................7:00amto4:00pmTuesday24January . . . . . . . . . . . . . . . . . . 7:30amto4:00pmWednesday25January...............7:30amto4:00pmThursday 26 January . . . . . . . . . . . . . . . . . . . . .7:30amtonoon

Interactive Paper and Symposium Demonstration Session

Interactive Paper Set-up, Viewing, and Presentations

Author Set-up:Monday 23 January . . . . . . . . . . . . . . . . . . . . . 8:00to10:00am

General Viewing:Monday 23 January and Tuesday24January . . . . . . . . . . . . . . . . . 10:00amto4:00pm

Interactive Paper Session:Tuesday24January . . . . . . . . . . . . . . . . . . . . . 5:30to8:00pm

Conference attendees are encouraged to attend the Interactive Paper and Symposium Demonstration Session where Interactive Paper authors display their posters and are available to answer questionsandengageinin-depthdiscussionsabouttheirpapers.Light refreshments areprovided.Pleasenote that conferenceregistrationbadgesarerequiredforentranceandthatpostersmay be previewed by all attendees beginning Monday/Tuesday 10:00amto4:00pm. Authorsareaskedtosetuptheirposterpapersbetween8:00and10:00amonMonday.Pushpinsareprovided;othersuppliescan be obtained at the Conference Registration Desk. Posters will be on display Monday and Tuesday. Authors must remove poster papers at the conclusion of the InteractiveSession; posters not removed are consideredunwanted and will be removed by staff and discarded. Neither sponsoring Society assumes responsibility for posters left up before or after the Interactive Paper Session.

Symposium Demonstration Session:

Tuesday24January......................5:30to8:00pm

The highly-successful, interactive, hands-on demonstration of hardware, software, display, and research products related to all the topics coveredby theElectronic ImagingSymposiumwill again take place in conjunction with the Interactive Papers session. This annual demonstration—which traditionally has showcased the largest and most diverse collection of stereoscopic research andproductsinonelocation—representsauniquenetworkingopportunity, a time when attendees can see the latest research in action, compare commercial products, ask questions oftechnically knowledgeable demonstrators, and even make purchasingdecisionsaboutarangeofEIproducts.

All-Conference ReceptionWednesday25January......................7:00to9:00pm

The All-Conference Reception provides a wonderful opportunity togettoknowandinteractwithElectronicImagingcolleagues.Plan to join us for this relaxing and enjoyable event.

3D TheatreMonday 23 January . . . . . . . . . . . . . . . . . . . . . . 5:30to7:30pm

View the latest in 3D content from around the world in a large-screen format at this very popular session, part of the Stereoscopic Displays and Applications conference. 3D glasses provided.


Plenary Presentations

Tuesday24January

Computational PhotographyWilliam T. Freeman, Massachusetts Institute of Technology

Abstract: Computational Photography explores the design space at the interaction of optics, sensing, and computation. I’ll review my favorite research projects within this area, most of them by other people, and a few that I was involved with. These projects involve modifications to the

camera lens, aperture, shutter, light source or image sensor. By designing algorithms appropriate for each camera modification, novel image capture or manipulation capabilities can be achieved. Biography: William T. Freeman is Professor and Associate DepartmentHeadof theElectricalEngineeringandComputerScience Department at the Computer Science and Artificial IntelligenceLaboratory(CSAIL)atMIT,joiningthefacultyin2001.

Wednesday 25 January

More Words and Bigger PicturesDavid Forsyth, Univ. of Illinois at Urbana-Champaign

Abstract: I will sketch the current state of the art in object recognition, with a particular emphasis on methods that try to tag images with words, phrases or sentences. Methods are built on two strong ideas: local image descriptors,

and classification. Using these tools, the field has built rich technologies for classifying images of objects, detecting objects in images, and describing unfamiliar objects in images. Current methods are moderately accurate. Future methods will have higher accuracy, will produce richer and more conceptual descriptions, and will exploit geometric context to understand spatial relations between objects. Biography: David Forsyth is currently a full professor at Univeristy of Illinois at Urbana-Champaign, where he moved from UC Berkeley and was also full professor. He has published over 130 papers on computer vision, computer graphics and machine learning.Mr.Forsythhasservedasprogramco-chairforIEEEComputer Vision and Pattern Recognition in 2000 and in 2011, general co-chair for CVPR 2006, and program co-chair for the EuropeanConferenceonComputerVision2008.Heisaregularmember of the program committee of all major international conferences on computer vision. He has served five years on the SIGGRAPH program committee and continues to be a regular reviewer. Mr. Forsyth has received best paper awards at the InternationalConferenceonComputerVisionandattheEuropeanConferenceonComputerVision.HereceivedanIEEEtechnicalachievementawardfor2005forhisresearchandbecameanIEEEfellowin2009.Hisrecenttextbook,“ComputerVision:AModernApproach” (joint with J. Ponce and published by Prentice Hall) is now widely adopted as a course text. A second edition is in press.

Plenary Session and Society Award PresentationsTuesday24January . . . . . . . . . . . . . . . . . . . . . 8:20to9:30am

Welcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8:20to8:25am

Plenary Presentation . . . . . . . . . . . . . . . . . . . . . 8:25to9:10am

Society Award Announcements . . . . . . . . . . . . 9:10to9:20am

Plenary Session and Conference Award PresentationsWednesday 25 January . . . . . . . . . . . . . . . . . . . 8:20to9:30am

Welcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8:20to8:25am

Plenary Presentation . . . . . . . . . . . . . . . . . . . . . 8:25to9:10am

Conference Award Announcements . . . . . . . . . 9:10to9:20am


Conference Daily Schedule

SUNDAY | MONDAY | TUESDAY | WEDNESDAY | THURSDAY

3D Imaging, Interaction, and Measurement

8288 Stereoscopic Displays and Applications XXIII (Woods, Holliman, Favalora) p. 8

82903D Image Processing (3DIP) and Applications 2012 (Baskurt, Sitnik) p. 16

8289The Engineering Reality of Virtual Reality 2012 (McDowall, Dolinsky)p.14

Imaging, Visualization, and Perception

8291Human Vision and Electronic Imaging XVII (Rogowitz, Pappas, de Ridder)p.19

8294Visualization and Data Analysis 2012 (Wong, Kao, Hao, Chen)p.29

8292Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications (Eschbach, Marcu, Rizzi) p. 23

8293Image Quality and System Performance IX (Gaykema, Burns) p. 26

Image Processing

8296Computational Imaging X (Bouman, Pollak, Wolfe) p. 36

8297Document Recognition and Retrieval XIX (Viard-Gaudin, Zanibbi)p.37

Digital Imaging Sensors and Applications

8301 Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques (Röning, Casasent)p.45

8298Sensors, Cameras, and Systems for Industrial/Scientific Applications XIII (Widenhorn, Nguyen, Dupret)p.39

Multimedia Processing and Applications

8295AImage Processing: Algorithms and Systems X (Egiazarian, Agaian, Gotchev) p. 32

8295BParallel Processing for Imaging Applications II (Recker, Wang) p. 35

8300 Image Processing: Machine Vision Applications V (Bingham, Lam)p.43

8302 Imaging and Printing in a Web 2.0 World III (Lin, Allebach, Fan)p.47

8303 Media Watermarking, Security, and Forensics XIV (Memon, Alattar, Delp)p.49

8304AMultimedia on Mobile Devices 2012 (Creutzburg, Akopian) p. 51

8304BMultimedia Content Access: Algorithms and Systems VI (Snoek, Sebe, Kennedy) p. 53

Visual Information Processing and Communication

8305 Visual Information Processing and Communication III (Said, Guleryuz, Stevenson) p. 55

8299Digital Photography VIII (Battiato, Rodricks, Sampat)p.41


Conference 8288Monday-Wednesday 23-25 January 2012 • Proceedings of SPIE Vol. 8288

Stereoscopic Displays and Applications XXIIIConference Chairs: Andrew J. Woods, CurtinUniv.(Australia);Nicolas S. Holliman, DurhamUniv.(UnitedKingdom);Gregg E. Favalora, Optics for Hire (United States)

Founding Chair: John D. Merritt, The Merritt Group (United States)

Program Committee: Neil A. Dodgson, Univ.ofCambridge(UnitedKingdom);Hideki Kakeya, Univ.ofTsukuba(Japan);Takashi Kawai, WasedaUniv.(Japan);John D. Stern, IntuitiveSurgical,Retired(UnitedStates);Vivian K. Walworth, StereoJet,Inc.(UnitedStates);Chris Ward, LightspeedDesign,Inc.(UnitedStates);Michael A. Weissman, Consultant(UnitedStates);Samuel Zhou, IMAX Corp. (Canada)

Monday 23 JanuarySESSION 1 . . . . . . . . . . . . . . . . . . . . . .Mon. 8:30 to 9:10 am

3D ApplicationsSession Chair: Andrew J. Woods, Curtin Univ. (Australia)

Matching stereo 3D reconstructions of CT/MRI data and intraoperative stereo video for medical education and treatment planning, Justus F. Ilgner M.D., Martin Westhofen M.D., Univ. Hospital Aachen (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-01]

Stereoscopic desktop VR system for tele-maintenance, Michael Kleiber,FraunhoferFKIE(Germany) . . . . . . . . . . . . . . . . . . . . . . .[8288-02]

Welcome and Opening Remarks . . . .Mon. 9:10 to 9:20 am

Session Chair: Andrew J. Woods, Curtin Univ. (Australia)

Keynote Presentation I . . . . . . . . Mon. 9:20 to 10:20 amThe SD&A Keynote Presentations provide an opportunity to hear an eminent speaker discuss a topic of interest to the global stereoscopic community. Speaker and topic to be announced. For updated information, visit spie.org/SDA.

SESSION 5 . . . . . . . . . . . . . . . . Mon. 10:50 am to 12:30 pm

3D DevelopmentsSession Chair: Neil A. Dodgson, Univ. of Cambridge (United Kingdom)

Sessions 2 and 5 run concurrently.

Stereoscopic-3D display design: a new paradigm with Intel adaptive stable image technology [IA-SIT], Sunil K. Jain, Intel Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-16]

A real-time misalignment correction algorithm for stereoscopic 3D cameras,IbrahimE.Pekkucuksen,BuyueZhang,AzizUmitBatur,TexasInstruments Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-17]

Full-color stereoscopy with little flicker at low-refresh rate by time-division multiplexing anaglyph, Hideki Kakeya, Hiroaki Kodaira, Univ. of Tsukuba (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-18]

Supervised disparity estimation, Patrick Vandewalle, Chris Varekamp, Philips Research Nederland B.V. (Netherlands) . . . . . . . . . . . . . .[8288-19]

Analysis of brain activity and response during monoscopic and stereoscopic visualization,EnricoCalore,RaffaellaFolgieri,DavideGadia, Univ. degli Studi di Milano (Italy) . . . . . . . . . . . . . . . . . . . .[8288-20]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


3D Cameras and Mobile 3DSession Chair: Michael A. Weissman, Consultant (United States)


Angle-sensitive pixels: a new paradigm for low-power, low-cost 2D and 3D sensing, Albert Wang, Sheila S. Hemami, Alyosha Molnar, Cornell Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-03]

Polarizing aperture stereoscopic cinema camera,LennyLipton,Oculus3D (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-04]

Hardware-efficient, real-time 3D image processing for single lens color/depth-unified sensor: from depth noise reduction, depth super-resolution, to stereoscopic image synthesis,HwasupLim,YongSunKim,OukChoi,ByongminKang,Seong-JinKim,KeechangLee,JamesD.K. Kim, Changyeong Kim, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-05]

Unassisted 3D camera calibration, Kalin Atanassov, Vikas Ramachandra, Sergio Goma, Qualcomm Inc. (United States) . . . . . . . . . . . . . . .[8288-06]

Auto convergence for stereoscopic 3D mobile cameras,BuyueZhang,Sreeni Kothandaraman, Aziz Umit Batur, Texas Instruments Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-07]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


SESSION 3 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:20 pm

Autostereoscopic Displays: Multi-Layer and Multi-Projector

Session Chair: Gregg E. Favalora, Optics for Hire (United States)


Beyond parallax barriers: applying formal optimization methods to multi-layer automultiscopic displays,DouglasLanman,MassachusettsInstitute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8288-08]

3D image quality of 200-inch glasses-free 3D display system, MasahiroKawakita,NHKScience&TechnicalResearchLabs.(Japan);Shoichiro Iwasawa, National Institute of Information and Communications Technology(Japan);MasahisaSakai,YasuyukiHaino,MasahitoSato,JVCKENWOODHoldings,Inc.(Japan);NaomiInoue,NationalInstituteofInformation and Communications Technology (Japan). . . . . . . . .[8288-09]

Implementation and analysis of an autostereoscopic display using multiple liquid crystal layers, Hironobu Gotoda, National Institute of Informatics (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-10]

360-degree, three-dimensional table-screen display using small array of high-speed projectors, Shigeki Uchida, Yasuhiro Takaki, Tokyo Univ. of Agriculture and Technology (Japan) . . . . . . . . . . . . . . . . . . . . .[8288-11]

SESSION 6 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:20 pm

Perception, Quality, and ComfortSession Chair: John D. Stern, Intuitive Surgical, Inc., Retired (United

States)


Motion in-depth constancy in stereoscopic displays,SidrahLaldin,LaurieWilcox,CarlyHylton,RobertS.Allison,YorkUniv. (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-21]

Quality evaluation of depth image-based rendering methods for stereoscopic video content,MattiasEisenbarth,TechnischeUniv.Wien(Austria)andemotion3D(Austria);FlorianH.Seitner,emotion3D(Austria)andTechnischeUniv.Wien(Austria);MargritGelautz,TechnischeUniv.Wien (Austria) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-22]

Disparity profiles in 3DV applications: overcoming the issue of heterogeneous viewing conditions in stereoscopic delivery, Guillaume Boisson, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . .[8288-23]

Investigation of content characteristics for visual comfort assessment in stereoscopic images,Seong-ilLee,YongJuJung,HosikSohn,HyunWook Park, Yong Man Ro, KAIST (Korea, Republic of) . . . . . . . .[8288-24]

Conference 8288

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Mon. 3:50 to 5:10 pm

3D Image Processing and Content AdaptationSession Chair: Nicolas S. Holliman, Durham Univ. (United Kingdom)


Focus mis-match detection in stereoscopic content, Frederic Devernay, Sergi Pujades, Vijay Ch.A.V., INRIA Rhône-Alpes (France) . . . .[8288-12]

2D-to-3D image conversion: leveraging 3D data on the net, Janusz Konrad, Geoffrey Brown, Meng Wang, Prakash Ishwar, Boston Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-13]

3D cinema to 3DTV content adaptation,DidierDoyen,LasithYasakethu,LaurentBlondé,QuanHuynh-Thu,TechnicolorS.A.(France) . . .[8288-14]

A stereoscopic movie player with real-time content adaptation to the display geometry,SylvainDuchene,INRIARhône-Alpes(France);MartinLambers,Univ.Siegen(Germany);FredericDevernay,INRIARhône-Alpes(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-15]

SESSION 7 . . . . . . . . . . . . . . . . . . . . . Mon. 3:50 to 5:10 pm

AutostereoscopySession Chair: Gregg E. Favalora, Optics for Hire (United States)


History of autostereoscopic cinema, Walter Funk, Hologlyphics (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-25]

Full optical characterization of auto-stereoscopic 3D displays using local viewing angle and imaging measurements, Pierre M. Boher, ThierryLeroux,ThibaultBignon,ELDIM(France) . . . . . . . . . . . . .[8288-26]

Analysis on monocular accommodation in horizontal-parallax-only super-multiview display, Jisoo Hong, Youngmin Kim, Seoul National Univ.(Korea,Republicof);Jae-HyeungPark,ChungbukNationalUniv.(Korea,Republicof);ByounghoLee,SeoulNationalUniv.(Korea,Republicof) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-27]

A novel time-multiplexed, autostereoscopic, multi-view, full-resolution 3D display,Jian-ChiunLiou,IndustrialTechnologyResearchInstitute(Taiwan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-28]

3D Theatre . . . . . . . . . . . . . . . . . . . Mon. 5:30 to 7:30 pmSession Chairs: Andrew J. Woods, CurtinUniv.(Australia);

Chris Ward, LightspeedDesign,Inc.(UnitedStates)

This ever-popular session allows attendees to see large-screen examples of 3D content from around the world. Program announced at the conference. 3D glasses provided.

SD&A Annual Dinner . . . . . . . . . . Mon. 7:45 to 10:00 pmThe annual informal dinner for SD&A attendees. An opportunity to meet with colleagues and discuss the latest advances. There is no host for the dinner. Information on venue and cost will be provided on the day at the conference.


Tuesday 24 JanuaryPlenary Session and Society Award Presentations . . . Tues. 8:20 to 9:30 amComputational Photography, William T. Freeman, Massachusetts Institute of Technology (United States)

Keynote Presentation II . . . . . . . Tues. 9:30 to 10:30 amThe SD&A Keynote Presentations provide an opportunity to hear an eminent speaker discuss a topic of interest to the global stereoscopic community. Speaker and topic to be announced. For updated information,visittheSPIEhomepageforSD&A.

SESSION 8 . . . . . . . . . . . . . . . . Tues. 11:00 am to 12:40 pm

3D Image Quality: CrosstalkSession Chair: John O. Merritt, The Merritt Group (United States)

Crosstalk reduces the amount of depth seen in 3D images of natural scenes,InnaTsirlin,RobertS.Allison,LaurieM.Wilcox,YorkUniv.(Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-29]

Method and simulation to study 3D crosstalk perception, Darya AleksandrovnaKhaustova,LaurentBlondé,DidierDoyen,QuanHuynh-Thu, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-30]

Reproducibility of crosstalk measurements on active glasses 3D LCD displays based on temporal characterization, Sylvain Tourancheau, Mid SwedenUniv.(Sweden);KunWang,AcreoAB(Sweden)andMidSwedenUniv.(Sweden);LucjanJanowski,JaroslawBulat,AGHUniv.ofScienceandTechnology(Poland);KjellBrunnström,AcreoAB(Sweden);MarcusBarkowsky, Polytech’ Nantes (France) . . . . . . . . . . . . . . . . . . . . .[8288-31]

Crosstalk and brightness in projection-based, multi-view systems, Roland Blach, Achim Pross, Fraunhofer-Institut für Arbeitswirtschaft undOrganisation(Germany);AlexanderKulik,BauhausUniv.Weimar(Germany);OliverStefani,Fraunhofer-InstitutfürArbeitswirtschaftundOrganisation (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-32]

How much crosstalk can be allowed in a stereoscopic system at various grey levels?, Sergey A. Shestak, Dae-Sik Kim, Samsung ElectronicsCo.,Ltd.(Korea,Republicof) . . . . . . . . . . . . . . . . . . .[8288-33]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:40to2:00pm

SESSION 9A . . . . . . . . . . . . . . . . . . . . Tues. 2:00 to 3:20 pm

Stereoscopic 3D Image Quality: Quantifying Perception and Comfort: Joint Session with

Conference 8291Session Chairs: Sergio R. Goma, QualcommInc.(UnitedStates);John

O. Merritt, TheMerrittGroup(UnitedStates);Christopher W. Tyler, TheSmith-KettlewellEyeResearchInstitute(UnitedStates);Lora T. Likova, TheSmith-KettlewellEyeResearchInstitute(UnitedStates)

Apparent stereo: the Cornsweet illusion can enhance perceived depth, PiotrDidyk,Max-Planck-InstitutfürInformatik(Germany);TobiasRitschel,ElmarEisemann,TelecomParisTech(France);KarolMyszkowski,Hans-Peter Seidel, Max-Planck-Institut für Informatik (Germany) . . . . .[8291-19]

Perceived depth of multi parallel, overlapping, transparent, stereoscopic surfaces, Saori Aida, Koichi Shimono, Tokyo Univ. of MarineScienceandTechnology(Japan);WaJamesTam,CommunicationsResearch Ctr. Canada (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-20]

Diagnosing perceptual distortion present in group stereoscope viewing, Brice B. Pollock, Jonathan W. Kelly, Melissa M. Burton, Stephen B.Gilbert,EliotWiner,IowaStateUniv.(UnitedStates) . . . . . . . .[8291-21]

Visual discomfort and the timing of vergence-accommodation conflicts, Joohwan Kim, David Kane, Martin S. Banks, Univ. of California, Berkeley (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-34]

SESSION 9B . . . . . . . . . . . . . . . . . . . . Tues. 3:50 to 5:10 pm




Measuring 3D discomfort from vertical and torsional disparities in natural images,ChristopherW.Tyler,LoraT.Likova,TheSmith-KettlewellEyeResearchInstitute(UnitedStates);KalinAtanassov,VikasRamachandra, Sergio Goma, Qualcomm (United States). . . . . . .[8291-22]

Visual fatigue versus eye-movements,CyrilVienne,LaurentBlondé,Didier Doyen, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . .[8288-35]

Visual comfort: stereoscopic objects moving in the horizontal and mid-sagittal planes,WaJamesTam,FilippoSperanza,CarlosVázquez,RonRenaud,CommunicationsResearchCtr.Canada(Canada);NamhoHur,ElectronicsandTelecommunicationsResearchInstitute(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-36]

Visual discomfort with stereo 3D displays when the head is not upright, David Kane, Robin Held, Martin Banks, Univ. of California, Berkeley (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-37]

Interactive Paper and Symposium Demonstration Session. . . . . . . . . . .Tues. 5:30 to 8:00 pm

Demonstrations . . . . . . . . . . . . . . . . . . . . . 5:30 to 8:00 pm A symposium-wide demonstration session will be open to attendees 5:30 to 8:00 pm Tuesday evening. Demonstrators will provide interactive, hands-on demonstrations of a wide-range of products related to Electronic Imaging.

The session will have a focused “Stereoscopic Displays and Applications” area. The demonstration session hosts a vast collection of stereoscopic products

providing a perfect opportunity to witness a wide array of stereoscopic displays with your own two eyes.

Posters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5:30 to 8:00 pm Interactive papers will be placed on display after 10:00 am on Monday. An interactive paper session, with authors present at their papers, will be held

Tuesday evening, 5:30 to 8:00 pm.

Interactive Papers: Stereoscopic Perception and QualityCorrelation between a perspective distortion in a S3D content and the visual discomfort perceived,DidierDoyen,LaurentBlondé,Jean-JacquesSacré,TechnicolorS.A.(France) . . . . . . . . . . . . . . . . . .[8288-54]

Evaluation of quality of experience in interactive 3D visualization: methodology and results,SylvainTourancheau,MårtenSjöström,RogerOlsson,MidSwedenUniv.(Sweden);AndersPersson,Ctr.forMedicalImageScienceandVisualization(Sweden);ThomasEricson,SetredAB(Sweden) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-55]

Objective view synthesis quality assessment, Pierre-Henri Conze, TechnicolorS.A.(France)andInstitutNationaldesSciencesAppliquéesdeRennes(France);PhilippeRobert,TechnicolorS.A.(France);LuceMorin,InstitutNationaldesSciencesAppliquéesdeRennes(France) . .[8288-56]

Depth enhancement of S3D content and the psychological effects, Masahiro Hirahara, Saki Shiraishi, Takashi Kawai, Waseda Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-57]

Perception of size and shape in stereoscopic 3D imagery, Michael D. Smith,MDSConsulting(UnitedStates);BradleyT.Collar,WarnerBros.EntertainmentInc.(UnitedStates). . . . . . . . . . . . . . . . . . . . . . . . .[8288-58]

Quality of experience model for 3DTV, Wei Chen, France Telecom R&D (France)andPolytech’Nantes(France);JérômeFournier,FranceTelecomR&D(France);MarcusBarkowsky,PatrickLeCallet,Polytech’Nantes(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-59]

Conference 8288


New approach and analysis on the 3D crosstalk for auto-stereoscopic displays,Sung-MinJung,Kyeong-JinLee,Ji-NaKang,Seung-ChulLee,Kyoung-MoonLim,LGDisplay(Korea,Republicof) . . . . . . . . . .[8288-60]

Towards adapting current 3DTV for an improved 3D experience, LaurentBlondé,DidierDoyen,CédricThébault,QuanHuynh-Thu,TechnicolorS.A.(France);DanielStoenescu,EmmanuelDaniel,Jean-LouisdeBougrenetdelaTocnaye,TELECOMBretagne(France);SamirBentahar,EyesTripleShut(France) . . . . . . . . . . . . . . . . . . . . . . . .[8288-61]

Interactive Papers: 3D DisplaysIntegral volumetric imaging with high-resolution and smooth-motion parallax, Shimpei Sawada, Hideki Kakeya, Univ. of Tsukuba (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-62]

Enlargement of viewing freedom of reduced-view SMV display, Junya Nakamura, Taichi Takahashi, Yasuhiro Takaki, Tokyo Univ. of Agriculture and Technology (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-63]

Development of high-speed, phase-modulating spatial light modulators for 3D-holographic displays, Hiroyuki Takagi, Taichi Goto, Alexander Baryshev, Mitsuteru Inoue, Toyohashi Univ. of Technology (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-64]

Color hologram generation using depth map of real objects with viewing-zone-angle expansion, Kosuke Nomura, Tokyo Univ. of Science (Japan) and National Institute of Information and Communications Technology(Japan);RyutaroOi,TaiichiroKurita,NationalInstituteofInformationandCommunicationsTechnology(Japan);TakayukiHamamoto, Tokyo Univ. of Science (Japan) . . . . . . . . . . . . . . . . .[8288-65]

Stereoscopic surround displays using interference filters, Silvio Peikert, Jérémie Gerhardt, Fraunhofer FIRST (Germany) . . . . . . .[8288-66]

Design of extended viewing zone at autostereoscopic 3D display based on diffusing optical element, Min-Chang Kim, Yong Seok Hwang, Eun-SooKim,KwangwoonUniv.(Korea,Republicof) . . . . . . . . .[8288-67]

Floating image device with auto-stereoscopic display and viewer-tracking technology,Chang-YingChen,Kun-LungTseng,Chy-LinWang,Chao-Hsu Tsai, Industrial Technology Research Institute (Taiwan) [8288-68]

A time-sequential, mutli-view, autostereoscopic display without resolution loss using a multi-directional backlight unit and an LCD panel, Hyunkyung Kwon, Hee-Jin Choi, Sejong Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-69]

Full-resolution autostereoscopic display with all-electronic tracking system,Jean-EtienneGaudreau,PolarScreens,Inc.(Canada) . .[8288-70]

Interactive Papers: Multiview Image MethodsNovel multi-view generation framework for 3D displays, Kyuyoung Hwang,YanghoCho,HoyoungLee,DusikPark,ChangYeongKim,Samsung Advanced Institute of Technology (Korea, Republic of) [8288-71]

Calibration of multiview camera with parallel and decentered image sensors, Mohamed Ali-Bey, Saïd Moughamir, Noureddine Manamanni, Univ. de Reims Champagne-Ardenne (France) . . . . . . . . . . . . . . .[8288-72]

Inversion-free multiview subpixel rendering for natural 3D presentation, Yun-Tae Kim, Gee-Young Sung, Ju-Yong Park, Dong-Kyung Nam, Du-Sik Park, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-73]

Wide-viewing angle three-dimensional display based on the ray reconstruction method using multiple micro-projectors, Hideya Takahashi,KentaHirooka,OsakaCityUniv.(Japan);KenjiYamada,OsakaUniv. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-74]

Multi-layered, see-through movie in diminished reality, Yuko Uematsu, Takanori Hashimoto, Takuya Inoue, Naoki Shimizu, Hideo Saito, Keio Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-75]

An efficient motion vector prediction for multiview video coding, Seungchul Ryu, Jungdong Seo, Kwanghoon Sohn, Yonsei Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-76]

Geometry compensation using depth and camera parameters for multi-view video coding, Dong-Hyun Kim, Jungdong Seo, Kwanghoon Sohn, Yonsei Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . .[8288-77]

Converting conventional stereo pairs to multi-view sequences using morphing, Roger Olsson, Vamsi Kiran Adhikarla, Sebastian Schwarz, MårtenSjöström,MidSwedenUniv.(Sweden). . . . . . . . . . . . . . .[8288-78]

Multiview video and depth compression for free-view navigations, Yuta Higuchi, Mehrdad Panahpour Tehrani, Tomohiro Yendo, Toshiaki Fujii, Masayuki Tanimoto, Nagoya Univ. (Japan) . . . . . . . . . . . . .[8288-79]

A layered inpainting method for virtual view synthesis, Seona Kim, KyoungJoonLee,SeoulNationalUniv.(Korea,Republicof);IlDongYun,HankukUniv.ofForeignStudies(Korea,Republicof);SangUkLee,SeoulNational Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . .[8288-80]

Analysis on ray reconstruction characteristics of multi-view and integral imaging display,Hee-SeungKim,Hyun-EuiKim,Kyeong-MinJeong, Jae-Hyeung Park, Chungbuk National Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-81]

A content-based method for perceptually driven joint color/depth compression,EmilieBosc,LuceMorin,MurielPressigout,InstitutNationaldesSciencesAppliquéesdeRennes(France) . . . . . . . . . . . . . . .[8288-82]

Interactive Papers: Stereoscopic Image MethodsVideo retargeting for stereoscopic content under 3D viewing constraints, Christel Chamaret, Technicolor S.A. (France) . . . . .[8288-83]

Efficient panoramic sampling of real-world environments for image-based stereoscopic telepresence,LuisE.Gurrieri,EricDubois,Univ.ofOttawa (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-84]

Partial 2D-to-S3D conversion and the cognitive characteristics, Yoshihisa Koido, Takashi Kawai, Waseda Univ. (Japan) . . . . . . .[8288-85]

Disparity-compensated view synthesis for S3D content correction, Robert Philippe, Cédric Thébault, Valter Drazic, Pierre-Henri Conze, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-86]

Virtual view interpolation at arbitrary view points for mixed-resolution 3D videos,SeungsinLee,SeokLee,Ho-CheonWey,Du-SikPark,Samsung Advanced Institute of Technology (Korea, Republic of) [8288-87]

Dense blur map estimation for real-time 2D-to-3D conversion,LucVosters,TechnischeUniv.Eindhoven(Netherlands)andAxonDigitalDesign(Netherlands);GerarddeHaan,PhilipsResearchNederlandB.V.(Netherlands)andTechnischeUniv.Eindhoven(Netherlands) . . .[8288-88]

ROI-based transmission method for stereoscopic video to maximize rendered 3D video quality,ChamindaT.E.R.Hewage,MariaG.Martini,Kingston Univ. (United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . .[8288-89]

Stereoscopic image-inpainting-based, view-synthesis algorithm for glasses-based and glasses-free 3D displays, Chang Yuan, Sharp Labs.ofAmerica,Inc.(UnitedStates);ChrisHueiHungLiao,TheUniv.ofSouthernCalifornia(UnitedStates);HaoPan,SharpLabs.ofAmerica,Inc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-90]

Towards a real-time, high-definition depth sensor with hardware-efficient stereo matching,KeZhang,IMEC(Belgium)andKatholiekeUniv.Leuven(Belgium);GuanyuYi,Chao-KangLiao,ChristineLin,Hsiu-ChiYeh,IMEC(Belgium);RudyLauwereins,IMEC(Belgium)andKatholiekeUniv.Leuven(Belgium);LucVanGool,KatholiekeUniv.Leuven(Belgium)andETHZurich(Switzerland);GauthierLafruit,IMEC (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-91]

Interactive floating windows: a new technique for stereoscopic video games,AndrewHogue,BillKapralos,ChrisZerebecki,MinaTawadrous,Brodie Stanfield, Univ. of Ontario Institute of Technology (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-92]

Stereoscopic reconfiguration for 3D displays, Jean-Christophe Houde, Pierre-Marc Jodoin, Univ. de Sherbrooke (Canada) . . . . . . . . . . .[8288-93]

Dual-pupil 3D imaging system through complementary multiband bandpass filters: modeling to reduce color rivalry and characterization of the depth range,SamYoungsamBae,JetPropulsionLab.(UnitedStates)andTheUniv.ofSouthernCalifornia(UnitedStates);AllenReam,MontanaStateUniv.(UnitedStates);RonaldKorniski,MichaelShearn,JetPropulsionLab.(UnitedStates);HrayrShahinian,SkullBaseInstitute(UnitedStates);HarishManohara,JetPropulsionLab.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-94]

Conference 8288


Interactive Papers: Stereoscopic ApplicationsAn immersive virtual reality environment to enable science innovation, DennisChau,BradleyMcGinnis,JonasTalandis,JasonLeigh,Univ.ofIllinoisatChicago(UnitedStates);TomPeterka,AaronKnoll,AslihanSumer,ArgonneNationalLab.(UnitedStates) . . . . . . . . . . . . . . .[8288-95]

Interactive stereoscopic visualization of large-scale astrophysical simulations,RalfKaehler,SLACNationalAcceleratorLab.(UnitedStates)[8288-96]

Designing stereoscopic information visualization for 3D-TV: what can we can learn from S3D gaming?, Jonas Schild, Maic Masuch, Univ. Duisburg-Essen(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-97]

Wednesday 25 JanuaryPlenary Session and Conference Award Presentations . . . . . . . . . . . Wed. 8:20 to 9:30 amMore Words and Bigger Pictures, David A. Forsyth, Univ. of Illinois at Urbana-Champaign (United States)

SESSION 10 . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

3D GamesSession Chair: Chris Ward, LightspeedDesign,Inc.(UnitedStates)

Case study: the introduction of stereoscopic games on the Sony PlayStation 3,IanH.Bickerstaff,SonyComputerEntertainmentEuropeLtd.(UnitedKingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-38]

Stereoscopic 3D video games and their effects on engagement, AndrewHogue,BillKapralos,ChrisZerebecki,MinaTawadrous,BrodieStanfield, Univ. of Ontario Institute Of Technology (Canada) . . . .[8288-39]

Stereoscopic display in a slot machine,MikkoLaakso,Finland’sSlotMachine Association (RAY) (Finland) . . . . . . . . . . . . . . . . . . . . . . .[8288-40]

Conference 8288

SESSION 12 . . . . . . . . . . . . . . . Wed. 11:10 am to 12:30 pm

Autostereoscopic Displays: Advances and AnalysisSession Chair: Hideki Kakeya, Univ. of Tsukuba (Japan)


Floating three-dimensional display with 360-degree viewing angle, Daisuke Miyazaki, Kenta Okoda, Yuki Maeda, Takaaki Mukai, Osaka City Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-45]

A novel 3D display system using combined integral imaging and Fresnel hologram, Jhen-Si Chen, Neil Collings, Daping Chu, Univ. of Cambridge (United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-46]

Analysis and management of geometric distortions on multi-view displays with only horizontal parallax, Amir Said, Bruce Culbertson, Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . . . . . .[8288-47]

Mixed-resolution view synthesis using non-local means refined image merging,ThomasRichter,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany);MichaelSchöberl,Friedrich-AlexanderUniv.Erlangen-Nürnberg(Germany);JürgenSeiler,TobiasTröger,AndréKaup,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany) . . . . . . . . . . . . . .[8288-48]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


3D CinemaSession Chair: Samuel Zhou, IMAX Corp. (Canada)


Energia 3D: a feature documentary case study,EnriqueCriado,EnxebreEntertainment(Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-41]

YouDash3D: exploring stereoscopic 3D gaming for 3D movie theaters, JonasSchild,Univ.Duisburg-Essen(Germany);SvenSeele,HochschuleBonn-Rhein-Sieg(Germany);MaicMasuch,Univ.Duisburg-Essen(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-42]

3D storytelling: a case study (Invited Paper),KasimirLehto,4thWallProductions (Finland). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-43]

Thinking in z-space: flatness and spatial narrativity,RayZone,The3-DZone(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-44]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:40to2:00pm


SESSION 13 . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 4:20 pm

Stereoscopic DisplaysSession Chair: Takashi Kawai, Waseda Univ. (Japan)

Investigating the cross-compatibility of IR-controlled active shutter glasses, Andrew J. Woods, Jesse Helliwell, Curtin Univ. (Australia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-49]

New high-brightness interference filter developments, Helmut Jorke, Arnold Simon, Infitec GmbH (Germany) . . . . . . . . . . . . . . . . . . . .[8288-50]

Real-world stereoscopic performance in multiple-focal-planes displays: how far apart should the image planes be?, Simon J. Watt, KevinJ.MacKenzie,LouiseC.Ryan,BangorUniv.(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-51]

An eyeglass-like, eye-tracked, optical see-through, head-mounted display using freeform optics, Hong Hua, College of Optical Sciences, The Univ. of Arizona (United States) . . . . . . . . . . . . . . . . . . . . . . .[8288-52]

Optimization of a multi-view system based on pulsed LED-LCD projectors, Achim Pross, Roland Blach, Matthias Bues, Roman Reichel, Oliver Stefani, Fraunhofer-Institut für Arbeitswirtschaft und Organisation (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-53]

Discussion Forum . . . . . . . . . . . . . . . Wed. 4:20 to 5:20 pm The SD&A Discussion Forum is a great opportunity to hear a panel of stereoscopic luminaries discuss a topic of high stereoscopic relevance. Moderator and panelists to be announced. For updated information, visit www.spie.org/SDA

SD&A Closing Remarks . . . . . . . . . . Wed. 5:20 to 5:30 pmPlease visit www.stereoscopic.org for more information about the Stereoscopic Displays and Applications conference.

Conference 8288


Conference8289Tuesday-Wednesday 24-25 January 2012 • Proceedings of SPIE Vol. 8289

The Engineering Reality of Virtual Reality 2012Conference Chairs: Ian E. McDowall, FakespaceLabs,Inc.(UnitedStates);Margaret Dolinsky, Indiana Univ. (United States)

Tuesday 24 JanuaryPlenary Session and Society Award Presentations . . . . . . . . . . Tues. 8:20 to 9:30 amComputational Photography, William T. Freeman, Massachusetts Institute of Technology (United States)

SESSION 1 . . . . . . . . . . . . . . . . . . . . Tues. 9:30 to 10:30 am

Context Awareness and ImmersionSession Chair: Ian E. McDowall, FakespaceLabs,Inc.(UnitedStates)

Foreign language learning in immersive virtual environments, Benjamin Chang,LeeSheldon,MeiSi,RensselaerPolytechnicInstitute(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-01]

Virtual reality technology prevents accidents in extreme situations, YehudaBadihi,JerusalemCollegeofTechnology(Israel);MottiReiff,Jerusalem College of Technology (Korea, Republic of) . . . . . . . .[8289-02]

Motion parallax in immersive cylindrical display systems, Nicolas Filliard,GillesReymond,RenaultTechnocentre(France);AndrasKemeny,RenaultTechnocentre(France)andArtsetMétiersParisTech(France);Alain Berthoz, Collège de France (France) . . . . . . . . . . . . . . . . . .[8289-03]


Communicating Perspective through VRSession Chair: Margaret Dolinsky, Indiana Univ. (United States)

Meta!Blast computer game: a pipeline from science to 3D art to education,EveSyrkinWurtele,P.J.Campbell,WilliamSchneller,DianeBassham, Iowa State Univ. (United States). . . . . . . . . . . . . . . . . .[8289-04]

Learning immersion without getting wet, Julieta C. Aguilera, Adler Planetarium & Astronomy Museum (United States) . . . . . . . . . . .[8289-05]

Byte me,DianeGromala,MeehaeSong,AndreaZeffiro,SimonFraserUniv. (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-06]

Female artists and the VR crucible: expanding the aesthetic vocabulary,JacquelynF.Morie,TheUniv.ofSouthernCalifornia(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-07]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Tues. 2:00 to 3:20 pm

Refacing VRSession Chair: Ian E. McDowall, FakespaceLabs,Inc.(UnitedStates)

Markerless 3D facial motion capture system, Youngkyoo Hwang, Jung-Bae Kim, Won-Chul Bang, James D.K. Kim, Chang-Yeong Kim, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . .[8289-08]

Capturing geometry in real-time using a tracked Microsoft Kinect, Daniel Tenedorio, Marlena Fecho, Jorge Schwartzhaupt, Robert Pardridge, JamesLue,JurgenP.Schulze,Univ.ofCalifornia,SanDiego(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-09]

An example-based face relighting, Hyunjung Shim, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . .[8289-10]

Heteronyms and avatars: a self-reflective system for artistic activity, ElifE.Ayiter,SabanciUniv.(Turkey) . . . . . . . . . . . . . . . . . . . . . . .[8289-11]


VR Hybrids: Augmented RealitySession Chair: Todd Margolis, Univ. of California, San Diego (United

States)

ManifestAR: an augmented reality manifesto, John Craig Freeman, EmersonCollege(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . .[8289-12]

Invisible waves and hidden realms: augmented reality and experimental art, Silvia P. Ruzanka, Rensselaer Polytechnic Institute (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-13]

Immersive realities: the transition from VR to AR as an artistic medium, Todd Margolis, Tracy Cornish, Univ. of California, San Diego (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-14]

MetaTree: augmented reality narrative explorations of urban forests, Ruth G. West, Todd Margolis, Univ. of California, San Diego (United States);JarlathO’Neil-Dunne,TheUniv.ofVermont(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-15]





Prediction of visually perceived location using reaching action and effect of reaching distance on it, Masahiro Suzuki, Keigo Takazawa, Kazutake Uehira, Kanagawa Institute of Technology (Japan) . . . .[8289-23]

An innovative multimodal virtual platform for communication with devices in a natural way, Chhayarani R. Kinkar, Richa Golash, Akhilesh R. Upadhyay, Sagar Institute of Research, Technology & Science (India) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-24]

Composite lay-up process with application of elements of augmented reality,JozefNovak-Marcincin,JozefBarna,MiroslavJanak,LudmilaNovakova-Marcincinova, Veronika Fecova, Technical Univ. of Kosice (Slovakia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-25]


Conference8289


SESSION 5 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Virtuality, Affect and CognitionSession Chair: Ian E. McDowall, FakespaceLabs,Inc.(UnitedStates)

Transforming 3D virtual reality: paintings through navigation, Margaret Dolinsky, Indiana Univ. (United States) . . . . . . . . . . . . . . . . . . . . .[8289-16]

Affect and the visceral: the reality of the virtual,PatrickM.Lichty,Columbia College Chicago (United States) . . . . . . . . . . . . . . . . . .[8289-17]

The cognitive implications of virtual locomotion with a restricted field of view,WilliamE.Marsh,JonathanW.Kelly,VeronicaJ.Dark,JamesH.Oliver, Iowa State Univ. (United States) . . . . . . . . . . . . . . . . . . . .[8289-18]

SESSION 6 . . . . . . . . . . . . . . . . Wed. 11:10 am to 12:30 pm

Educational Pathways in VRSession Chair: Margaret Dolinsky, Indiana Univ. (United States)

Use of a simulator based on virtual reality to assess the application of economic driving techniques by truck drivers, Tales N. Bogoni, Univ. EstadualdoMatoGrossoSul(Brazil);MárcioSarrogliaPinho,PUCRS-IPCT (Brazil) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-19]

LVC interaction within a mixed-reality training system, Brice B. Pollock, Iowa State Univ. (United States) and Virtual Reality Application Ctr. (United States);EliotWiner,StephenGilbert,IowaStateUniv.(UnitedStates);JuliodelaCruz,HectorGonzalez,U.S.ArmyRDECOM/STTC(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-20]

Immersive volume rendering of blood vessels,GregoryLong,HanSukKim, Alison Marsden, Yuri Bazilevs, Jurgen Schulze, Univ. of California, San Diego (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8289-21]

A virtual reality interface for pre-planning of surgical operations based on a customized model of the patient, Marcin Witkowski, Robert Sitnik, JanuszLenar,WarsawUniv.ofTechnology(Poland) . . . . . . . . . .[8289-22]


Conference8290Tuesday-Thursday 24-26 January 2012 • Proceedings of SPIE Vol. 8290

3D Image Processing (3DIP) and Applications 2012Conference Chairs: Atilla M. Baskurt, Univ.ofLyon(France);Robert Sitnik, Warsaw Univ. of Technology (Poland)

Program Committee: Mongi A. Abidi, TheUniv.ofTennessee(UnitedStates);Hugues Benoit-Cattin, INSERM(France);Adrian G. Bors, The Univ. ofYork(UnitedKingdom);Saida Bouakaz, Univ.ofLyon(France);Mohamed Daoudi, TELECOMLille1(France);Eduardo da Silva, Univ. Federal doRiodeJaneiro(Brazil);Jean-Luc E. Dugelay, EURECOM(France);Florent Dupont, Univ.ofLyon(France);Afzal Godil, National Institute of StandardsandTechnology(UnitedStates);Benoît M. Macq, Univ.CatholiquedeLouvain(Belgium);Serge Miguet, Univ.ofLyon(France);Levent Onural, BilkentUniv.(Turkey);Eric Paquet, NationalResearchCouncilCanada(Canada);Marc Pollefeys, The Univ. of North Carolina at Chapel Hill (UnitedStates);William Puech, Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France);Bülent Sankur, Bogaziçi Üniv. (Turkey);Peter Schelkens, VrijeUniv.Brussel(Belgium);Michela Spagnuolo, ConsiglioNazionaledelleRicerche(Italy);Frédéric Truchetet, Univ. de Bourgogne(France);Stefano Tubaro, Politecnico di Milano (Italy)



Stereo and Multiview Imaging ISession Chair: Afzal Godil, National Institute of Standards and

Technology (United States)

Edge-aware stereo matching with O(1) complexity, Cevahir Cigla, MiddleEastTechnicalUniv.(Turkey)andVestek(Turkey);A.AydinAlatan,MiddleEastTechnicalUniv.(Turkey) . . . . . . . . . . . . . . . . . . . . . .[8290-01]

Establishing eye contact for home video communication using stereo analysis and free viewpoint synthesis, Christian Weigel, Technische Univ.Ilmenau(Germany);NiklasTreutner,Humboldt-Univ.zuBerlin(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-02]

Depth adaptive hierarchical hole filling for DIBR-based 3D videos, Mashhour Solh, Ghassan Al-Regib, Georgia Institute of Technology (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-03]

Space carving MVD sequences for modelling natural 3D scenes, Youssef Alj, Technicolor S.A. (France) and Institut National des Sciences AppliquéesdeRennes(France);GuillaumeBoisson,TechnicolorS.A.(France);LuceMorin,MurielPressigout,InstitutNationaldesSciencesAppliquéesdeRennes(France);PhilippeBordes,TechnicolorS.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-04]


Poster PopsSession Chair: Robert Sitnik, Warsaw Univ. of Technology (Poland)

In addition to their interactive paper presentations, the interactive paper authors will provide short oral presentations during the

conference.


Stereo and Multiview Imaging IISession Chair: Afzal Godil, National Institute of Standards and

Technology (United States)

A locally content-dependent filter for inter-perspective anti-aliasing, MårtenSjöström,SylvainTourancheau,XushengWang,RogerOlsson,MidSweden Univ. (Sweden) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-05]

Photometric and geometric rectification for stereoscopic images, Seung-RyongHan,JongsulMin,SamsungElectronicsCo.,Ltd.(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-06]





Novel time- and depth-stamped imaging for 3D-PIV (particle image velocimetry) using correlation image sensor, Kenji Komiya, Toru Kurihara, Shigeru Ando, The Univ. of Tokyo (Japan) . . . . . . . . . .[8290-40]

3D imaging for ballistics analysis using chromatic white-light sensor, AndreyMakrushin,MarioHildebrandt,JanaDittmann,EricClausing,Otto-von-Guericke-Univ.Magdeburg(Germany);RobertFischer,ClausVielhauer, Univ. of Applied Sciences Brandenburg (Germany) . . .[8290-41]

Computer-aided 3D-shape construction of hearts from CT images for rapid prototyping, Yutaro Kato, Masayuki Fukuzawa, Nobuyuki Nakamori, KyotoInstituteofTechnology(Japan);SeiichiroOzawa,KyotoPrefecturalUniv.ofMedicine(Japan);IsaoShiraishi,NationalCardiovascularCtr.Research Institute (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-42]

Operation-free 3D visualization of pulsatile tissues in freehand ultrasonic diagnosis, Kazumasa Kawata, Masayuki Fukuzawa, Nobuyuki Nakamori,KyotoInstituteofTechnology(Japan);YoshikiKitsunezuka,Saiseikai Hyogo-ken Hospital (Japan) . . . . . . . . . . . . . . . . . . . . . .[8290-43]

Semiautomatic generation of semantic building models from image series, Stefan Wirtz, Peter Decker, Denes Weiß, Dietrich Paulus, Univ. Koblenz-Landau(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-44]

Complex virtual urban environment modeling from CityGML data and OGC web services: application to the SIMFOR project, Jean-Christophe Chambealland,GillesGesquière,Lab.desSciencesdel’InformationetdesSystèmes (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-45]

Liquid crystal materials and structures for image processing and 3D shape acquisition, Katarzyna Garbat, Military Univ. of Technology (Poland);PiotrGarbat,WarsawUniv.ofTechnology(Poland) . . .[8290-46]

Piece-wise linear function estimation for platelet-based depth maps coding using edge detection, Dorsaf Sebai, The Univ. of Manouba (Tunisia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-47]

Source modeling for effective 3D video delivery,ChamindaT.E.R.Hewage, Maria G. Martini, Kingston Univ. (United Kingdom) . . . .[8290-48]


New technique for capturing images containing invisible depth information on object using brightness modulated right, Sae Isaka, Kazutake Uehira, Kanagawa Institute of Technology (Japan) . . . .[8290-49]

Interactive 3D segmentation by tubular envelope model for thoracic aorta treatment,PawelJ.Lubniewski,Univ.d’AuvergneClermont-FerrandI (France) and Univ. Kardynala Stefana Wyszynskiego w Warszawie (Poland);BrunoMiguelM.D.,ChristopheLohou,Univ.d’AuvergneClermont-Ferrand I (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-50]

A parallel stereo reconstruction algorithm with applications in entomology (APSRA), Rajesh Bhasin, Univ. of Illinois at Urbana Champaign(UnitedStates);WonJunJang,JohnC.Hart,Univ.ofIllinoisatUrbana-Champaign (United States) . . . . . . . . . . . . . . . . . . . . . . .[8290-51]

Optical design methodology for igniting isotropic lights at two distinct geometric locations for 3D imaging camera development, Sabri Gurbuz, Masahiro Kawakita, National Institute of Information and Communications Technology (Japan) . . . . . . . . . . . . . . . . . . . . . .[8290-52]


SESSION 4 . . . . . . . . . . . . . . . . . Wed. 9:30 am to 12:30 pm

Time-Of-Flight Data, Depth Maps AnalysisSession Chair: Eric Paquet, National Research Council Canada

(Canada)

Depth map upscaling through edge-weighted optimization, Sebastian Schwarz,MårtenSjöström,RogerOlsson,MidSwedenUniv. (Sweden) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-07]

Adaptive switching filter for noise removal in highly corrupted depth maps from time-of-flight image sensors,SeungheeLee,KwanghyukBae,Kyu-MinKyung,Tae-ChanKim,SAMSUNGElectronicsCo.,Ltd.(Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-08]

Parametric model-based noise reduction for ToF depth sensors, Yong SunKim,ByongminKang,HwasupLim,OukChoi,KeechangLee,JamesD. K. Kim, Chang-Yeong Kim, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-09]

Silhouette extraction using color and depth information,EkaterinaV.Tolstaya,VictorBucha,SamsungElectronicsCo.,Ltd.(RussianFederation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-10]

Discrete and continuous optimizations for depth image super-resolution,OukChoi,HwasupLim,YongSunKim,ByongminKang,KeechangLee,JamesD.K.Kim,Chang-YeongKim,SamsungAdvancedInstitute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . .[8290-11]

A line-based approach for depth superresolution, Yongseok Soh, SeoulNationalUniv.(Korea,Republicof);Jae-YoungSim,UlsanNationalInstituteofScienceandTechnology(Korea,Republicof);Sang-UkLee,Seoul National Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . .[8290-12]

Efficient spatio-temporal hole filling strategy for Kinect depth maps, MassimoCamplani,LuisSalgado,Univ.PolitécnicadeMadrid (Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-13]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 5 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 5:40 pm

3D Shape Modeling, RetrievalSession Chair: Mohamed Daoudi, TELECOMLille1(France)

Experimental results of bispectral invariants discriminative power, KarolKubicki,JagiellonianUniv.(Poland);RamakrishnaKakarala,NanyangTechnological Univ. (Singapore) . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-14]

Evaluation of surface reconstruction from point clouds by shape parameters,LuCao,FonsJ.Verbeek,LeidenUniv.(Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-15]

3D mesh Reeb graph computation using commute-time and diffusion distances,RachidELKhoury,JeanPhilippeVandeborre,MohamedDaoudi,InstitutTELECOM(France)andTELECOMLille1 (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-16]

Geometric modeling of pelvic organs with thickness, Thierry Bay, Lab.desSciencesdel’InformationetdesSystèmes(France);ZhuoWeiChen,Univ.d’Evry-Vald’Essonne(France);RomainRaffin,MarcDaniel,Lab.desSciencesdel’InformationetdesSystèmes(France);PierreJoli,Univ.d’Evry-Vald’Essonne(France);ZhiQiangFeng,Marc-EmmanuelBellemare,Lab.desSciencesdel’InformationetdesSystèmes (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-17]

Refined facial disparity maps for automatic creation of 3D avatars, RafaelPagés,FranciscoMorán,LuisSalgado,Univ.PolitécnicadeMadrid(Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-18]

Fast human pose estimation using 3D Zernike descriptors, Daniel Berjón, Francisco Morán, Univ. Politécnica de Madrid (Spain) . . .[8290-19]

Analysis of binning of normals for spherical harmonic cross-correlation,RobertLarkins,MichaelJ.Cree,AdrianA.Dorrington,TheUniv.ofWaikato(NewZealand) . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-20]

Topology reconstruction for B-Rep modeling from 3D mesh in reverse engineering applications,RoselineBénière,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France)andC4W(France);GérardSubsol,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France);GillesGesquière,Lab.desSciencesdel’InformationetdesSystèmes(France);FrançoisLeBreton,C4W(France);WilliamPuech,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France) . . . . . . . . . . . . . . . . . .[8290-21]

An evaluation of local shape descriptors for 3D shape retrieval, Sarah Y.Tang,PrincetonUniv.(UnitedStates);AfzalGodil,NationalInstituteofStandards and Technology (United States) . . . . . . . . . . . . . . . . .[8290-22]

Thursday 26 JanuarySESSION 6 . . . . . . . . . . . . . . . . . . . Thurs. 8:30 to 10:10 am

3D Analysis, Feature Extraction, SegmentationSession Chair: Atilla M. Baskurt, Univ.ofLyon(France)

Description of 3D textures: a fractal and probabilistic approach based on non-differentiability,EricPaquet,NationalResearchCouncilCanada(Canada);HernaL.Viktor,Univ.ofOttawa(Canada) . . . . . . . . . .[8290-23]

Spatial modeling of bone microarchitecture,HuiLi,KangLi,TaehyongKim,AidongZhang,MuraliRamanathan,Univ.atBuffalo(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-24]

A new affine invariant method for image matching, Philippe Montesinos,EcoledesMinesd’Alès(France) . . . . . . . . . . . . . . .[8290-25]

2D-3D feature association via projective transform invariants for model-based 3D pose estimation, Osman S. Gedik, A. Aydin Alatan, MiddleEastTechnicalUniv.(Turkey) . . . . . . . . . . . . . . . . . . . . . .[8290-26]

Reprocessing anaglyph images, Henry G. Dietz, Univ. of Kentucky (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-27]

Conference8290


SESSION 7 . . . . . . . . . . . . . . . Thurs. 10:50 am to 12:10 pm

3D MetrologySession Chair: Robert Sitnik, Warsaw Univ. of Technology (Poland)

Measurement of micro-motions within non-transparent small objects using grayscale information in x-ray stereo projection imaging, Wasil H. M. Salih, Jan A. N. Buytaert, Joris J. J. Dirckx, Univ. Antwerpen (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-28]

A stereoscopic imaging system for laser back scatter-based trajectory measurement in ballistics: part 2, Uwe Chalupka, Hendrik Rothe, Helmut-Schmidt-Univ. (Germany) . . . . . . . . . . . . . . . . . . .[8290-29]

Single frame coaxial 3D measurement using depth from defocus of projection system, Toru Kurihara, Shigeru Ando, The Univ. of Tokyo (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-30]

Multidirectional four-dimensional shape measurement system, Janusz Lenar,RobertSitnik,MarcinWitkowski,WarsawUniv.ofTechnology(Poland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-31]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to1:50pm

SESSION 8 . . . . . . . . . . . . . . . . . . . . Thurs. 1:50 to 3:30 pm

3D Imaging SystemsSession Chair: Frédéric Truchetet, Univ. de Bourgogne (France)

Estimation of surface normal vectors based on 3D scanning from heating approach,OlivierAubreton,Univ.deBourgogne(France);GonenEren,GalatasarayÜniv.(Turkey);FredericTruchetet,Univ.deBourgogne(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-32]

First topographical features for the age determination of latent biometric fingerprint traces using a 3D optical and contact-less chromatic white light (CWL) sensor, Ronny Merkel, Otto-von-Guericke-Univ.Magdeburg(Germany);StefanGruhn,FachhochschuleBrandenburg(Germany);JanaDittmann,Otto-von-Guericke-Univ.Magdeburg(Germany);ClausVielhauer,FachhochschuleBrandenburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-33]

A single-imager, single-lens video camera prototype for 3D imaging, LaurenChristopher,WeixuLi,IndianaUniv.-PurdueUniv.Indianapolis(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-34]

3D multimodal data fusion system, Piotr Garbat, Warsaw Univ. of Technology (Poland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-35]

Fully automatic 3D digitization of unknown objects using progressive data bounding box,AntoineAigueperse,SouhaielKhalfaoui,Lab.d’Electronique,InformatiqueetImage(France);RalphSeulin,YohanFougerolle, David Fofi, Univ. de Bourgogne (France) . . . . . . . . . .[8290-36]


3D Compression and WatermarkingSession Chair: William Puech, Lab.d’InformatiquedeRobotiqueetde

MicroelectroniquedeMontpellier(France)

3D video compression with the H.264 codec,NikolausL.Karpinsky,SongZhang,IowaStateUniv.(UnitedStates) . . . . . . . . . . . . . . .[8290-37]

3D multiresolutions synchronization scheme based on feature point selection,NicolasTournier,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France)andStratégiesS.A.(France);WilliamPuech,GérardSubsol,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France);Jean-PierrePedeboy,Stratégies S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8290-38]

A content-adaptive scheme for reduced-complexity, multiview video coding, Aykut Avci, Jan De Cock, Roel Beernaert, Jelle De Smet, Univ. Gent(Belgium);YouriMeuret,VrijeUniv.Brussel(Belgium);PeterLambert,Herbert De Smet, Univ. Gent (Belgium). . . . . . . . . . . . . . . . . . . . .[8290-39]

Conference8290


Conference8291Monday-Thursday 23-26 January 2012 • Proceedings of SPIE Vol. 8291

Human Vision and Electronic Imaging XVIIConference Chairs: Bernice E. Rogowitz, VisualPerspectivesConsulting(UnitedStates);Thrasyvoulos N. Pappas, Northwestern Univ. (United States);Huib de Ridder, Technische Univ. Delft (Netherlands)

Program Committee: Albert J. Ahumada, Jr., NASAAmesResearchCtr.(UnitedStates);Jan P. Allebach, PurdueUniv.(UnitedStates);Erhardt Barth, Univ.zuLübeck(Germany);Walter R. Bender, MITMediaLab.(UnitedStates);Michael H. Brill, Datacolor(UnitedStates);John C. Dalton, SynthetikSoftware(UnitedStates);Scott J. Daly, DolbyLabs.,Inc.(UnitedStates);Tiarna Doherty, J.PaulGettyMuseum(UnitedStates);Elena A. Fedorovskaya, EastmanKodakCo.(UnitedStates);James Fewerda, RochesterInstituteofTechnology(UnitedStates);Jennifer Gille, Qualcomm Inc.(UnitedStates);Sheila S. Hemami, CornellUniv.(UnitedStates);Laurent Itti, TheUniv.ofSouthernCalifornia(UnitedStates);Stanley A. Klein, Univ.ofCalifornia,Berkeley(UnitedStates);Patrick Le Callet, Univ.deNantes(France);Lora T. Likova, TheSmith-KettlewellEyeResearchInstitute(UnitedStates);John J. McCann, McCannImaging(UnitedStates);Jeffrey B. Mulligan, NASAAmesResearchCtr.(UnitedStates);Karol Myszkowski, Max-Planck-InstitutfürInformatik(Germany);Adar Pelah, TheUniv.ofYork(UnitedKingdom);Eliezer Peli, SchepensEyeResearchInstitute(UnitedStates);Sylvia C. Pont, TechnischeUniv.Delft(Netherlands);Hawley K. Rising III, Consultant(UnitedStates);Sabine Süsstrunk, EcolePolytechniqueFédéraledeLausanne(Switzerland);Christopher W. Tyler, TheSmith-KettlewellEyeResearchInstitute(UnitedStates);Andrew B. Watson, NASA Ames Research Ctr. (United States)

Monday 23 JanuaryConference Welcome . . . . . . . . . . . . .Mon. 9:30 to 9:40 am

Session Chair: Bernice E. Rogowitz, Visual Perspectives Consulting (United States)

Keynote Session . . . . . . . . . . . . Mon. 9:40 am to 12:10 pmSession Chairs: Bernice E. Rogowitz, Visual Perspectives Consulting (UnitedStates);Thrasyvoulos N. Pappas, Northwestern Univ. (United

States);Huib de Ridder, Technische Univ. Delft (Netherlands)

The general solution to HDR rendering, John J. McCann, McCann Imaging (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-60]

Measuring material perception,LaurenceT.Maloney,NewYorkUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-61]

Computational photography and the Stanford Frankencamera, Marc S. Levoy,StanfordUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . .[8291-62]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm

SESSION 1 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:40 pm

Computational PhotographySession Chair: Erhardt Barth, Univ.zuLübeck(Germany)

Image representations learned for natural images and a non-linear maximum synthesis rule with applications in computational photography,JensHocke,ErhardtBarth,ThomasMartinetz,Univ.zuLübeck(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-01]

How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series, Thomas Binder, Florian Kriener, ChristianWichner,ManualWille,NikSoftwareGmbH(Germany);MikeWellner,ThomasKaester,ErhardtBarthPatternRecognitionLab. (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-02]

Metric image mosaics with bounded error, Dev Ghosh, John Tumblin, Northwestern Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . .[8291-03]

Single-lens 3D camera with extended depth of field, Christian Perwass, LennartWietzke,RaytrixGmbH(Germany) . . . . . . . . . . . . . . . . .[8291-04]

3D holoscopic video imaging system, Johannes H. Steurer, Arri Cine Technik (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-05]

SESSION 2 . . . . . . . . . . . . . . . . . . . . . Mon. 4:10 to 5:50 pm

Material PerceptionSession Chairs: Sylvia C. Pont, TechnischeUniv.Delft(Netherlands);

James A. Ferwerda, Rochester Institute of Technology (United States)

Predictive rendering for accurate material perception, Kavita Bala, Cornell Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-06]

From color to appearance in the real world,FrancisLamy,X-Rite,Inc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-07]

Towards material literacy: making perception and knowledge of materials explicit through visual and verbal documentation of material engagement,Ann-SophieLehmann,UtrechtUniv.(Netherlands)[8291-08]

Mixing material modes, Sylvia C. Pont, Technische Univ. Delft (Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-09]

Tangible display systems: bringing virtual objects into the real world, James A. Ferwerda, Rochester Institute of Technology (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-10]

Human Vision and Electronic Imaging Banquet . . . . . . . . . . . . . . . . . . . .Mon. 7:00 to 10:30 pm

For updated information, please visit www.spie.org/ei



Perceptual Image QualitySession Chair: Thrasyvoulos N. Pappas, Northwestern Univ. (United

States)

Quality estimation for images and video with different spatial resolutions,A.MuratDemirtas,Univ.ofCalifornia,Irvine(UnitedStates);AmyR.Reibman,AT&TLabs.Research(UnitedStates) . . . . . . .[8291-11]

Automatic parameter prediction for image denoising algorithms using perceptual quality features, Anish Mittal, Anush Krishna Moorthy, Alan Conrad Bovik, The Univ. of Texas at Austin (United States) . . . . .[8291-12]

Viewer preferences for classes of noise removal algorithms for high-definition content,SachinG.Deshpande,SharpLabs.ofAmerica,Inc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-13]

Image quality assessment in the low-quality regime, Guilherme O. Pinto, Sheila S. Hemami, Cornell Univ. (United States) . . . . . . . .[8291-14]



Multisensory Integration and Brain PlasticitySession Chair: Lora T. Likova, TheSmith-KettlewellEyeResearch

Institute (United States)

The question of simultaneity in multisensory integration,MarkE.McCourt,LynnetteLeone,NorthDakotaStateUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-15]

Multisensory integration deficits in children with autism spectrum disorders: a behavioral and ERP investigation, Clifford D. Saron, Yukari Takarae, Margarita Beransky, David M. Horton, Ashley Stark, Andrea Schneider, Fernanda Vieira, Susan M. Rivera, Univ. of California, Davis (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-16]

The spatiotopic ‘visual’ cortex of the blind,LoraT.Likova,TheSmith-KettlewellEyeResearchInstitute(UnitedStates) . . . . . . . . . . . . .[8291-17]

Acoustic-tactile rendering of visual information, Pubudu Madhawa Silva,ThrasyvoulosN.Pappas,NorthwesternUniv.(UnitedStates);JoshuaAtkins,JamesE.West,TheJohnsHopkinsUniv.(UnitedStates) [8291-18]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 5A . . . . . . . . . . . . . . . . . . . . Tues. 2:00 to 3:20 pm




Apparent stereo: the Cornsweet illusion can enhance perceived depth, PiotrDidyk,Max-Planck-InstitutfürInformatik(Germany);TobiasRitschel,ElmarEisemann,TelecomParisTech(France);KarolMyszkowski,Hans-Peter Seidel, Max-Planck-Institut für Informatik (Germany) . . . . .[8291-19]

Perceived depth of multi parallel, overlapping, transparent, stereoscopic surfaces, Saori Aida, Koichi Shimono, Tokyo Univ. of MarineScienceandTechnology(Japan);WaJamesTam,CommunicationsResearch Ctr. Canada (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-20]

Diagnosing perceptual distortion present in group stereoscope viewing, Brice B. Pollock, Jonathan W. Kelly, Melissa M. Burton, Stephen B.Gilbert,EliotWiner,IowaStateUniv.(UnitedStates) . . . . . . . .[8291-21]

Visual discomfort and the timing of vergence-accommodation conflicts, Joohwan Kim, David Kane, Martin S. Banks, Univ. of California, Berkeley (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-34]

SESSION 5B . . . . . . . . . . . . . . . . . . . . Tues. 3:50 to 4:10 pm




Measuring 3D discomfort from vertical and torsional disparities in natural images,ChristopherW.Tyler,LoraT.Likova,TheSmith-KettlewellEyeResearchInstitute(UnitedStates);KalinAtanassov,VikasRamachandra, Sergio Goma, Qualcomm (United States). . . . . . .[8291-22]

Visual fatigue versus eye-movements,CyrilVienne,LaurentBlondé,Didier Doyen, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . .[8288-35]

Visual comfort: stereoscopic objects moving in the horizontal and mid-sagittal planes,WaJamesTam,FilippoSperanza,CarlosVázquez,RonRenaud,CommunicationsResearchCtr.Canada(Canada);NamhoHur,ElectronicsandTelecommunicationsResearchInstitute(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-36]

Visual discomfort with stereo 3D displays when the head is not upright, David Kane, Robin Held, Martin Banks, Univ. of California, Berkeley (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8288-37]





Interactive Papers: Art and PerceptionThe effect of vibration on the data processing of gigapixel images of large cultural heritage objects,JayArreO.Toque,JunKaneko,YusukeMurayama,AriIde-Ektessabi,KyotoUniv.(Japan) . . . . . . . . . . . .[8291-48]

Structural analysis of digital sculptures and artefacts to guide heritage conservation,JerryC.Podany,J.PaulGettyMuseum(UnitedStates);Vadim Shapiro, Univ. of Wisconsin-Madison (United States) . . . .[8291-49]

Tracking of aging process by multiple 3D scans analysis,ErykBunsch,TheWilanówPalaceMuseum(Poland);RobertSitnik,WarsawUniv.ofTechnology (Poland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-50]

Aesthetics and entropy: optimization of brightness distribution, Melville R. V. Sahyun, Consultant (United States) . . . . . . . . . . . . .[8291-51]

A novel visualization tool for art history: a method for automated colorization of black and white archival photographs of works of art,SotiriosTsaftaris,InstituteforAdvancedStudiesLucca(Italy)andNorthwesternUniv.(UnitedStates);FrancescaCasadio,KristinLister,IngeFiedler,GwénaëlleGautier,TheArtInstituteofChicago(UnitedStates);Jean-LouisAndral,MuséePicasso(France);StephanieD’Alessandro,TheArtInstituteofChicago(UnitedStates);AggelosKatsaggelos,Northwestern Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . .[8291-52]

PHOG analysis of self-similarity in aesthetic images, Seyed Ali Amirshahi, Michael Koch, Joachim Denzler, Christoph Redies, Friedrich-Schiller-Univ. Jena (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-53]

Interactive Papers: Perception and Image QualityInfluence of the source contact and encoding configuration on the preceived quality for scalable video coding, Yohann Pitrey, Univ. de Nantes(France);MarcusBarkowsky,Polytech’Nantes(France);RomualdPepion,Univ.deNantes(France);PatrickLeCallet,Polytech’Nantes(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-54]

Evaluation of desktop interface displays for 360-degree video, Stephen B. Gilbert, Wutthigrai Boonsuk, Jonathan W. Kelly, Iowa State Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-55]

An evaluation of different setups for simulating lighting characteristics, Bart A. Salters, Michael J. Murdoch, Dragan Sekulovksi, Pieter Seuntiens, Shih-Han Chen, Philips Research Nederland B.V. (Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-56]

Conference8291


Biological visual attention guided automatic image segmentation with application in satellite imaging, Md I. Sina, Ana-Maria Cretu, Pierre Payeur, Univ. of Ottawa (Canada) . . . . . . . . . . . . . . . . . . . . . . . . .[8291-57]

A neurobiologically-based, two-stage model for human color vision, Charles Q. Wu, Stanford Univ. (United States) . . . . . . . . . . . . . . .[8291-58]

The oscillatory activities and its synchronization in auditory-visual integration as revealed by event-related potentials to bimodal stimuli, JiaGuo,BeijingNormalUniv.(China);PengXu,GeneralHospitalArmedPoliceForces(China);XiaojieZhao,BeijingNormalUniv.(China) [8291-59]


SESSION 6 . . . . . . . . . . . . . . . . . Wed. 9:30 am to 12:10 pm

Medical Image Quality: Features, Tasks and Semantics

Session Chair: Patrick Le Callet, Univ. de Nantes (France)

On the development of expertise in interpreting medical images (Invited Paper),ElizabethKrupinsky,TheUniv.ofArizona(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-23]

Modeling observer performance for optimizing image acquisition and processing,CraigK.Abbey,MiguelEckstein,Univ.ofCalifornia,SantaBarbara (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-24]

Comparison of HVS models’ conformities to radiologists’ sensation-perception behavioral performances on detection task for medical image quality assessment,LuZhang,ChristineCavaro-Ménard,Univ.ofAngers(France);PatrickLeCallet,Polytech’Nantes(France) . . .[8291-25]

Perceptual challenges to computer-aided diagnosis, Yulei Jang, The Univ. of Chicago (United States) . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-26]

Satisfaction of search experiments in advanced imaging, Kevin S. Berbaum, The Univ. of Iowa Hospitals and Clinics (United States)[8291-27]

Integrating human- and computer-based approaches to feature extraction and analysis,BerniceE.Rogowitz,VisualPerspectives(UnitedStates);AlyssaGoodman,Harvard-SmithsonianCtr.forAstrophysics(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-28]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm

SESSION 7A . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm

Visual Attention: Task and Image Quality: Joint Session with Conference 8293

Session Chair: Bernice E. Rogowitz, Visual Perspectives Consulting (United States)

How the task changes the way we watch images: a case of change detection and quality estimation,JenniRadun,TuomasLeisti,ToniVirtanen,GöteNyman,Univ.ofHelsinki(Finland) . . . . . . . . . . . . .[8293-20]

Measuring saliency in images: which experimental parameters for the assessment of image quality?, Clement Fredembach, Geoff Woolfe, Jue Wang,CanonInformationSystemsResearchAustraliaPty.Ltd. (Australia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-21]

Examining the effect of task on viewing behavior in videos using saliency maps, Hani Alers, Judith A. Redi, Technische Univ. Delft (Netherlands);IngridHeynderickx,PhilipsResearch(Netherlands)[8291-29]

Spontaneous observer adjusted colors: color balance and salient objects in images,ToniVirtanen,Univ.ofHelsinki(Finland);AriSiren,NokiaCo.(Finland);MikkoKuhna,AaltoUniv.SchoolofScienceandTechnology(Finland);JaakkoAiraksinen,OlliOrenius,JenniRadun,Univ.ofHelsinki(Finland);MikkoNuutinen,AaltoUniv.SchoolofScienceandTechnology(Finland);TimoSäämänen,GöteNyman,Univ.ofHelsinki(Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-22]

SESSION 7B . . . . . . . . . . . . . . . . . . . . Wed. 3:50 to 5:50 pm


Session Chair: Susan P. Farnand, Rochester Institute of Technology (United States)

Investigations of the tone reproduction curves on the perceived image quality for fine art reproductions, Jun Jiang, Franziska Frey, Susan Farnand, Rochester Institute of Technology (United States) . . . .[8293-23]

Characterizing eye movements during temporal- and global-quality assessment of h.264 compressed video sequences, Claire Mantel, NathalieGuyader,PatriciaLadret,GeluIonescu,Gipsa-lab(France);Thomas Kunlin, STMicroelectronics (France) . . . . . . . . . . . . . . . .[8291-30]

A compressed sensing model of crowding in peripheral vision, Jens Hocke,Univ.zuLübeck(Germany);MichaelDorr,SchepensEyeResearchInstitute(UnitedStates);ErhardtBarth,Univ.zuLübeck (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-31]

Foveated self-similarity in nonlocal image filtering, Alessandro Foi, TampereUniv.ofTechnology(Finland);GiacomoBoracchi,PolitecnicodiMilano (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-32]

A statistical study of the correlation between interest points and gaze points,MichaelNauge,Mohamed-ChakerLarabi,Univ.dePoitiers(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-33]

Interest point analysis as a model for the Poggendorrf illusion, Fred W. M.Stentiford,Univ.CollegeLondon(UnitedKingdom) . . . . . . . .[8291-34]


Art Theory, Perception, and RenderingSession Chair: Huib de Ridder, Technische Univ. Delft (Netherlands)

The perception of art and the science of perception (Invited Paper), Robert Pepperell, Cardiff School of Art and Design (United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-35]

Paintings, photographs, and computer graphics are calculated appearances, John J. McCann, McCann Imaging (United States)[8291-36]

Image integrity and aesthetics: towards a more encompassing definition of visual quality, Judith A. Redi, Technische Univ. Delft (Netherlands);IngridHeynderickx,PhilipsResearch(Netherlands)andDelftUniv. of Technology (Netherlands) . . . . . . . . . . . . . . . . . . . . . . . .[8291-37]

Depicting 3D shape using lines (Invited Paper), Doug DeCarlo, Rutgers, The State Univ. of New Jersey (United States) . . . . . . . . . . . . . . .[8291-38]

Box spaces in pictorial space: linear perspective versus templates, Huib de Ridder, Sylvia C. Pont, Technische Univ. Delft (Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-39]

Warping realist art to ensure consistent perspective: a new software tool for art investigations, Yu-Sung Chang, Wolfram Research (United States);DavidG.Stork,RicohInnovations,Inc.(UnitedStates) .[8291-40]

Sound meets image: freedom of expression in texture description, ReinierJ.Jansen,RenévanEgmond,HuibdeRidder,TechnischeUniv.Delft(Netherlands);ThrasyvoulosN.Pappas,NorthwesternUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-41]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11:40amto1:00pm

Conference8291



Computer Vision and Image Analysis of ArtSession Chair: Christopher W. Tyler, TheSmith-KettlewellEyeResearchInstitute(UnitedStates);Tiarna Doherty, J. Paul Getty

Museum(UnitedStates);David Stone, Univ. of Delaware (United States)

On the dynamics of aesthetic appreciation (Invited Paper), Claus-Christian Carbon, Otto-Friedrich-Univ. Bamberg (Germany) . . . .[8291-42]

An experimental and theoretical analysis of the merits of ‘virtual cleaning’ of paintings,J.Delaney,NationalGalleryofArt(UnitedStates);A.Casini,IstitutodiFisicaApplicataNelloCarrara(Italy);L.Simonot,Univ.dePoitiers(France);M.Thoury,NationalGalleryofArt(UnitedStates);M.Picollo,L.Stefani,IstitutodiFisicaApplicataNelloCarrara(Italy);M.Poggesi,ConsiglioNazionaledelleRicerche(Italy);D.Conover,K.Fleisher,E.R.delaRie,NationalGalleryofArt(UnitedStates) . . . . . . . . .[8291-43]

In search of Leonardo: computer-based facial image analysis of Renaissance artworks for identifying Leonardo as subject, Christopher W.Tyler,TheSmith-KettlewellEyeResearchInstitute(UnitedStates);WilliamSmith,TheUniv.ofYork(UnitedKingdom);DavidG.Stork,RicohInnovations, Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-44]

Non-destructive analytical imaging of metallic surfaces using spectral measurements and ultrahigh-resolution scanning for cultural heritage investigation,JunKaneko,YusukeMurayama,JayArreToque,AriIde-Ektessabi,KyotoUniv.(Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-45]

Museum as an integrated imaging device: visualization of ancient Kyoto cityscape from folding screen artifact, Kimiyoshi Miyata, Umi Oyabu, Michihiro Kojima, National Museum of Japanese History (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-46]

Mapping colors from paintings to tapestries: rejuvenating the faded colors in tapestries based on colors in reference paintings,EijaJohansson,MarieStrom,ChalmersUniv.ofTechnology(Sweden);DavidG. Stork, Ricoh Innovations, Inc. (United States) . . . . . . . . . . . . .[8291-47]

Museum Visit: San Francisco Museum of Modern Art: Exhibition and Discussion . . . . .Thurs. 3:40 to 9:00 pm3:40to5:00pmTravel to San Francisco

5:00to7:00pmMuseum Tour

7:00pm No-Host Group Dinner

We will be visiting an exhibition at the San Francisco Museum of Modern Art and explore the current exhibit with the curator.

Participantswillleavetheconferencehotelat3:40pm.Transportation,fee details, restaurant, and exhibit information to be provided later.

Conference8291



Color Imaging XVII: Displaying, Processing, Harcopy, and ApplicationsConference Chairs: Reiner Eschbach, XeroxCorp.(UnitedStates);Gabriel G. Marcu, AppleInc.(UnitedStates);Alessandro Rizzi, Univ. degli Studi di Milano (Italy)

Program Committee: Jan P. Allebach, PurdueUniv.(UnitedStates);Scott J. Daly, DolbyLabs.,Inc.(UnitedStates);Phil J. Green, LondonCollegeofCommunication(UnitedKingdom);Roger D. Hersch, EcolePolytechniqueFédéraledeLausanne(Switzerland);Choon-Woo Kim, Inha Univ. (Korea,Republicof);Michael A. Kriss, Consultant(UnitedStates);Fritz Lebowsky, STMicroelectronics(France);Nathan Moroney, Hewlett-Packard Labs.(UnitedStates);Carinna E. Parraman, Univ.oftheWestofEngland(UnitedKingdom);Shoji Tominaga, ChibaUniv.(Japan);Stephen Westland, Univ.ofLeeds(UnitedKingdom)



Vision and HDR ISession Chair: Reiner Eschbach, Xerox Corp. (United States)

Spatiochromatic detection, appearance, and motivations in wide-gamut (Invited Paper),ScottJ.Daly,DolbyLabs.,Inc.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-01]

Color assimilation and contrast near absolute threshold (Invited Paper), John J. McCann, McCann Imaging (United States) . . . . . . . . . . .[8292-02]

Multi-illuminant color constancy for HDR images through exposure segmentation,HengZhang,HuapingLiu,OregonStateUniv.(UnitedStates);ShuxueQuan,BroadcomCorp.(UnitedStates) . . . . . . .[8292-03]


Vision and HDR IISession Chair: Alessandro Rizzi, Univ. degli Studi di Milano (Italy)

Tone mapping for HDR image with two separated luminance distributions, Masaki Kitaura, Fumio Okura, Masayuki Kanbara, Naokazu Yokoya, Nara Institute of Science and Technology (Japan) . . . . .[8292-04]

Color universal design: analysis of color category dependency on color vision type, Natsuki Kojima, Yasuyo G. Ichihara, Kogakuin Univ. (Japan);KeiIto,TheUniv.ofTokyo(Japan);MiyukiG.Kamachi,KogakuinUniv. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-05]

Colour perception with changes in levels of illumination, Kwame F. Baah,Dept.ofHealth(UnitedKingdom)andUniv.oftheArtsLondon(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-06]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to1:50pm


Color ManagementSession Chair: Gabriel G. Marcu, Apple Inc. (United States)

Reducing the number of calibration patterns for the two-by-two dot centering model,VahidBabaei,RomainRossier,RogerD.Hersch,EcolePolytechniqueFédéraledeLausanne(Switzerland) . . . . . . . . . . .[8292-07]

Spatial gamut mapping for preserving a detail by the regularization, In-Yong Song, Ho-Gun Ha, Wang-Jun Kyung, Yeong-Ho Ha, Kyungpook National Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . .[8292-08]

Evaluating color calibration kits with virtual display, Wei-Chung Cheng, Hugo Caceres, Aldo Badano, U.S. Food and Drug Administration (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-09]

Optimizing color fidelity in wide-gamut-display devices when processing images compressed by block-based DCT transforms, Fritz Lebowsky,STMicroelectronics(France) . . . . . . . . . . . . . . . . . . . .[8292-10]

Optimal gamut volume design for three primary and multiprimary display systems,CarlosEduardoRodriguez-Pardo,GauravSharma,Univ.ofRochester(UnitedStates);Xiao-FanFeng,JonSpeigle,IbrahimSezan,SharpLabs.ofAmerica,Inc.(UnitedStates) . . . . . . . . . . . . . . . .[8292-11]


The Dark Side of the ColorSession Chair: Reiner Eschbach, Xerox Corp. (United States)

The dark side of CIELAB,GauravSharma,CarlosEduardoRodriguez-Pardo, Univ. of Rochester (United States) . . . . . . . . . . . . . . . . . .[8292-12]

Complexitites of complex contrast,EliezerPeli,SchepensEyeResearchInstitute (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-13]

It’s not the pixel count, you fool, Michael A. Kriss, MAK Consultants (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-14]

Color imaging and aesthetics: is there the cheshire cat?,ElenaA.Fedorovskaya,EastmanKodakCo.(UnitedStates) . . . . . . . . . . .[8292-15]

Dark texture in artworks,CarinnaE.Parraman,Univ.oftheWestofEngland(UnitedKingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-16]

Harmonious colors: from alchemy to science, Giordano B. Beretta, NathanM.Moroney,Hewlett-PackardLabs.(UnitedStates) . . . .[8292-17]






Characterization of color scanners based on SVR,BinLi,YixinZhang,Jiangnan Univ. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-44]

The characterization of display based on RBF neural network,LixiaLi,YixinZhang,JiangnanUniv.(China) . . . . . . . . . . . . . . . . . . . . . . .[8292-45]

Deducing ink thickness variations of fluorescent print by a spectral prediction model,JuanQingWang,YixinZhang,JiangnanUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-46]

Robust least squares optimization for spectral Neugebauer model, Fang-Fang Han, Jiangnan Univ. (China) . . . . . . . . . . . . . . . . . . . .[8292-47]

Color sketch for toner saving,IliaV.Safonov,EkaterinaTolstaya,MichaelN.Rychagov,SamsungElectronicsCo.,Ltd.(RussianFederation);HoKeunLee,SangHoKim,DonchulChoi,SamsungElectronicsCo.,Ltd.(Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-48]

Reflectance model for recto-verso color halftone images, Juan Wang, ZhangYiXin,TianDongWen,JiangnanUniv.(China) . . . . . . . . .[8292-49]

The study on physical dot gain of second order FM halftone based on ink spreading in all ink superposition conditions, Shikun Xi, Jiangnan Univ. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-50]

Tensor decomposition for color printer model lookup table, Vishal Monga,ThePennsylvaniaStateUniv.(UnitedStates);MartyMaltz,ZhigangFan, Xerox Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-51]

Genetic algorithm for segmentation and classification of colony images automatically,WeishengLi,HenanPolytechnicUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-52]

Color edge detection using edge density, Weixing Wang, Henan Polytechnic Univ. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-53]

Spectral prediction model for variable dot-size ink jet presswork (Invited Paper), Weiyong Xing, Southern Yangtze Univ. (China) . .[8292-54]


SESSION 5 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Image Processing ISession Chair: Alessandro Rizzi, Univ. degli Studi di Milano (Italy)

Detection and compensation of backlight images using chrominance, HyungJunPark,SeongWookHan,SamsungElectronicsCo.,Ltd.(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-18]

The performance of image difference metrics for rendered HDR images, Jorn Skjerven, Ivar Farup, Gjøvik Univ. College (Norway)[8292-19]

A new method for skin color enhancement,HuanZhaoZeng,Hewlett-PackardCo.(UnitedStates);RonnierLuo,Univ.ofLeeds(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-20]


Image Processing IISession Chair: Fritz Lebowsky, STMicroelectronics (France)

CIE chromaticity, Planckian locus, and correlated color temperature estimation from raw-image data using colorchecker training images, Touraj Tajbakhsh, Technische Univ. Hamburg-Harburg (Germany)[8292-21]

Comparative performance analysis of mobile displays, Reza Safaee-Rad,QualcommInc.(Canada);MilivojeAleksic,QualcommInc.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-22]

Termites: a Retinex implementation based on a colony of agents, GabrieleSimone,GjøvikUniv.College(Norway);GiuseppeAudino,Univ.degliStudidiMilano(Italy);IvarFarup,GjøvikUniv.College(Norway);Alessandro Rizzi, Univ. degli Studi di Milano (Italy) . . . . . . . . . . . .[8292-23]

A color quantization algorithm based on minimization of L_p norm error in a modified CIELAB space, Haitao Xue, Jan P. Allebach, Charles A. Bouman, Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . .[8292-24]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to1:50pm

SESSION 7 . . . . . . . . . . . . . . . . . . . . . Wed. 1:50 to 3:10 pm

ApplicationsSession Chair: Jan P. Allebach, Purdue Univ. (United States)

Human skin imaging using three-phase spectral matching imager, AkiraKimachi,OsakaElectro-CommunicationUniv.(Japan);ShigeruAndo,TheUniv.ofTokyo(Japan);MotonoriDoi,ShogoNishi,OsakaElectro-Communication Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-25]

Automatically choosing the source daytime color image for colorization of night-vision images,ErolSarigul,YufengZheng,AlcornState Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-26]

Appearance analysis of human skin with cosmetic foundation, Rie Ohtsuki,KaneboCosmeticsInc.(Japan)andChibaUniv.(Japan);ShojiTominaga,ChibaUniv.(Japan);RieHikima,KaneboCosmeticsInc.(Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-27]

Color analysis and image rendering of woodblock prints with oil-based ink, Takahiko Horiuchi, Tetsushi Tanimoto, Shoji Tominaga, Chiba Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-28]

SESSION 8 . . . . . . . . . . . . . . . . . . . . . Wed. 3:40 to 5:20 pm

Printing and Halftoning ISession Chair: Carinna E. Parraman, Univ.oftheWestofEngland

(United Kingdom)

Theoretical analysis and demonstration of optical dot gain by the reflected image histogram, Mahziar Namedanian, Sasan Gooran, LinköpingUniv.(Sweden) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-29]

Pre-RIP color management for soft proofing, Ingeborg Tastl, Kok-Wei Koh,Hewlett-PackardLabs.(UnitedStates). . . . . . . . . . . . . . . . .[8292-30]

Parametrically controlled, stochastically seeded clustered halftones, EdgarAndresBernal,Shen-geWang,RobertP.Loce,XeroxCorp.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-31]

Assessing color reproduction tolerances in commercial print workflow,GiordanoB.Beretta,EricHoarau,SunilKothari,I-JongLin,JunZeng,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . .[8292-32]

Investigation of the paper dependency of laser-printed colors for uncoated papers, Saeideh Gorji Kandi, Institute for Color Science & Technology (Iran, Islamic Republic of) . . . . . . . . . . . . . . . . . . . . .[8292-33]

Conference8292



Printing and Halftoning IISession Chair: Shoji Tominaga, Chiba Univ. (Japan)

Color-dependent banding characterization and simulation on natural images,SiruiHu,JiaZhang,PurdueUniv.(UnitedStates);HilaNachlieli,DoronShaked,Hewlett-PackardLabs.IsraelLtd.(Israel);SmadarShiffman,IndigoLtd.(Israel);JanP.Allebach,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-34]

Modeling large-area influence in digital halftoning for electrophotographic printers,YanlingJu,XujieZhang,DhruvSaxena,PurdueUniv.(UnitedStates);TamarKashti,DrorKella,IndigoLtd.(Israel);DoronShaked,ManiFischer,Hewlett-PackardLabs.IsraelLtd.(Israel);RobertUlichney,Hewlett-PackardCo.(UnitedStates);JanP.Allebach,Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-35]

The octagon screen set: a square N-color, high-order, Moiré-free screen set,Yung-YaoChen,PurdueUniv.(UnitedStates);ManiFischer,Hewlett-PackardLabs.IsraelLtd.(Israel);TamarKashti,IndigoLtd.(Israel);DoronShaked,Hewlett-PackardLabs.IsraelLtd.(Israel);JanP.Allebach,Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-36]

Ink-saving strategy based on document content characterization and halftone textures, Maria V. Ortiz Segovia, Purdue Univ. (United States) andOcéPrintLogicTechnologies(France);NicolasBonnier,OcéPrintLogicTechnologies(France);JanP.Allebach,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-37]

Colour print workflow and methods for multi-layering of colour and decorative inks using UV inkjet for fine-art printing,CarinnaE.Parraman,PaulLaidler,Univ.oftheWestofEngland(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-38]

Halftone blending between smooth- and detail-screens to improve print quality with electrophotographic printers, Seong Jun Park, Purdue Univ.(UnitedStates);MarkQ.Shaw,GeorgeKerby,TerryNelson,Di-YuanTzeng,VictorLoewen,KurtBengtson,Hewlett-PackardCo.(UnitedStates);JanP.Allebach,PurdueUniv.(UnitedStates) . . . . . . . . .[8292-39]

SESSION 10 . . . . . . . . . . . . . . Thurs. 11:00 am to 12:20 pm

Spectral and DisplaySession Chair: Reiner Eschbach, Xerox Corp. (United States)

Spectral transmittance model for piles of transparencies printed in halftone,JacquesMachizaud,MathieuHébert,Lab.HubertCurien(France)andUniv.Jean-MonnetSaint-Etienne(France)andCNRS (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-40]

Optimal estimation of spectral reflectance based on metamerism, Tzren-RuChou,Wei-JuLin,NationalTaiwanNormalUniv. (Taiwan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-41]

Hue-shift model for DLP projector with the white peaking function, Il-Su Park, Ho-Gun Ha, Dae-Chul Kim, Yeong-Ho Ha, Kyungpook National Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-42]

Content-dependent noise reduction for mobile displays, Ga-Hee Kim,Yoon-GyooLee,Han-EolKim,Choon-WooKim,InhaUniv.(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8292-43]

Conference8292



Image Quality and System Performance IXConference Chairs: Frans Gaykema, OcéTechnologiesB.V.(Netherlands);Peter D. Burns, Consultant (United States)

Program Committee: Majed Chambah, Univ.deReimsChampagne-Ardenne(France);Luke C. Cui, LexmarkInternational,Inc.(UnitedStates);Mark D. Fairchild, RochesterInstituteofTechnology(UnitedStates);Susan P. Farnand, RochesterInstituteofTechnology(UnitedStates);Dirk W. Hertel, EInkCorp.(UnitedStates);Robin B. Jenkin, AptinaImagingCorp.(UnitedStates);Sang Ho Kim, SamsungDigitalCity(Korea,Republicof);Chaker Larabi, Univ.dePoitiers(France);Lindsay W. MacDonald, LondonCollegeofCommunication(UnitedKingdom);Yoichi Miyake, ChibaUniv.(Japan);Göte S. Nyman, Univ.ofHelsinki(Finland);D. René Rasmussen, QiAnalyticsLLC(UnitedStates);Sophie Triantaphillidou, Univ. of Westminster (UnitedKingdom);Eric K. Zeise, Kodak’sGraphicCommunicationsGroup(UnitedStates);Hongqin Zhang, Apple Inc. (United States)



Image Quality and Mobile Imaging I: Joint Session with Conference 8299

Session Chairs: Peter D. Burns, Carestream Health, Inc. (United States);Sebastiano Battiato, Univ. degli Studi di Catania (Italy)

Development of the CPIQ spatial metrics,HenrikEliasson,SonyEricssonMobileCommunicationsAB(Sweden);DonaldBaxter,STMicroelectronics(R&D)Ltd.(UnitedKingdom);FrédéricCao,DxOLabs(France);JonathanPhillips,EastmanKodakCo.(UnitedStates) .[8293-01]

A functional-design approach to lens shading correction issues on mobile camera system,SeunghunYoo,SAMSUNGElectronicsCo.,Ltd.(Korea,Republicof);TaeChanKim,SAMSUNGElectronicsCo.,Ltd.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-18]

Rethinking user interfaces for cameraphones, Stephen A. Brewster, Christopher McAdam, Univ. of Glasgow (United Kingdom) . . . . .[8299-19]


Image Quality and Mobile Imaging II: Joint Session with Conference 8299

Session Chairs: Peter D. Burns, Consultant(UnitedStates);Sebastiano Battiato, Univ. degli Studi di Catania (Italy)

Calibration and adaptation of ISO visual noise for camera phone image quality assessment, Donald J. Baxter, Andrew Murray, STMicroelectronics(R&D)Ltd.(UnitedKingdom) . . . . . . . . . . . . .[8293-02]

An objective method for evaluating the texture-preserving capability of digital camcorders,KongfengZhu,ShujunLi,DietmarSaupe,Univ.Konstanz (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-03]

Improving texture loss measurement: spatial frequency response based on a colored target, Uwe Artmann, Dietmar Wueller, Image EngineeringGmbH&Co.KG(Germany) . . . . . . . . . . . . . . . . . . .[8293-04]

On the performances of computer vision algorithms on mobile platforms,SebastianoBattiato,GiovanniM.Farinella,EnricoMessina,GiovanniPuglisi,DanieleRavì,Univ.degliStudidiCatania(Italy);Alessandro Capra, Valeria Tomaselli, STMicroelectronics (Italy) .[8299-20]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


Image Acquisition Performance: Characterization and Measurement

Session Chair: Robin B. Jenkin, Aptina Imaging Corp. (United States)

The uncertainty of scanner illumination II,LukeC.Cui,LexmarkInternational, Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . .[8293-05]

Measuring the modulation transfer function of image capture devices: what do the numbers really mean?,XujieZhang,YanlingJu,PurdueUniv.(UnitedStates);TamarKashti,DrorKella,TalFrank,IndigoLtd.(Israel);DoronShaked,Hewlett-PackardLabs.IsraelLtd.(Israel);RobertUlichney,Hewlett-PackardCo.(UnitedStates);ManiFischer,Hewlett-PackardLabs.IsraelLtd.(Israel);JanP.Allebach,PurdueUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-06]

A fast, automatic camera image stabilization benchmarking scheme, Jun Yu, Scott Craver, Binghamton Univ. (United States) . . . . . . .[8293-07]

A comparison of signal-to-noise ratio (SNR) of linear CCD sensors for optical payload,MahmoodWaqas,PakistanSpaceandUpperAtmospheric Research Commission (SUPARCO) (Pakistan) . . . .[8293-08]


Image Processing Performance: Characterization and Measurement

Session Chair: Sangho Kim, Samsung Digital City (Korea, Republic of)

A sharpness measure on automatically selected edge segments, Francesca Gasparini, Fabrizio Marini, Silvia Corchs, Schettini Raimondo, Univ. degli Studi di Milano-Bicocca (Italy) . . . . . . . . . . . . . . . . . . .[8293-09]

Selecting the proper window for SSIM, Steven McFadden, Univ. of Waterloo(Canada)andChristieDigitalSystemsCanada,Inc(Canada);Paul A. S. Ward, Univ. of Waterloo (Canada) . . . . . . . . . . . . . . . .[8293-10]

Measurement of texture loss for JPEG 2000 compression, Peter D. Burns,CarestreamHealth,Inc.(UnitedStates);DonWilliams,ImageScience Associates (United States) . . . . . . . . . . . . . . . . . . . . . . .[8293-11]

A no-reference image quality metric for blur and ringing distortions based on weighting process, Aladine Chetouani, Azeddine Beghdadi, Univ. Paris-Nord (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-12]






Optimal patch code design via device characterization, Wencheng Wu, EdulN.Dalal,XeroxCorp.(UnitedStates) . . . . . . . . . . . . . . . . . .[8293-37]

Influence of viewing device and soundtrack in HDTV on subjective video quality, Arne Redl, Christian Keimel, Klaus Diepold, Technische Univ. München (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-38]

Influence of viewing experience and stabilization phase in subjective video testing, Christian Keimel, Arne Redl, Klaus Diepold, Technische Univ. München (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-39]

Perceptual visual image sharpness metric for image-based imager stabilization,FabienF.G.Gavant,LaurentAlacoque,AntoineDupret,TienHo-Phuoc,DominiqueDavid,CEA-LETI(France) . . . . . . . . . . . . .[8293-40]

A unified method for comparison of algorithms of saliency extraction, TienHo-Phuoc,LaurentAlacoque,AntoineDupret,CEA-LETI(France);AnneGuérin-Dugué,Gipsa-lab(France);ArnaudVerdant,CEA-LETI(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-41]

Enhancement of halftoned images, Hyeon Seok Seo, Yuna Kim, Hea KeeLee,SangHoKim,DonChulChoi,SamsungElectronicsCo.,Ltd.(Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-42]


SESSION 5 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Image Display Performance: Color AdjustmentSession Chair: Sophie Triantaphillidou, Univ. of Westminster (United

Kingdom)

Comparative performance analysis of two picture adjustment methods: HSV versus YCbCr, Reza Safaee-Rad, Milivoje Aleksic, Qualcomm Inc. (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-13]

Evaluation of preferred lightness rescaling methods for color reproduction,YerinChang,PhilGreen,LondonCollegeofCommunication(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-14]

Investigations of the display white point on the perceived image quality, Jun Jiang, Farhad Abed, Joseph Voelkel, Rochester Institute of Technology (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-15]


Perceptual Image Quality ExperimentationSession Chair: D. René Rasmussen, QiAnalyticsLLC(UnitedStates)

Interactive, subjective image quality assessment, D. René Rasmussen, QiAnalyticsLLC(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-16]

Evaluation of perceived image sharpness with changes in the displayed image size,Jae-YoungPark,SophieTriantaphillidou,RalphE.Jacobson, Univ. of Westminster (United Kingdom) . . . . . . . . . . .[8293-17]

Towards a perceptual metric for computer-generated images, Pierre Boulenguez,BorisAirieau,Mohamed-ChakerLarabi,DanielMeneveaux,Univ. de Poitiers (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-18]

Assessing product image quality for online shopping, Anjan Goswami, SungH.Chung,NarenChittar,AtiqIslam,eBayInc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-19]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 7A . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm


Session Chairs: Bernice E. Rogowitz, Visual Perspectives Consulting (United States)

How the task changes the way we watch images: a case of change detection and quality estimation,JenniRadun,TuomasLeisti,ToniVirtanen,GöteNyman,Univ.ofHelsinki(Finland) . . . . . . . . . . . . .[8293-20]

Measuring saliency in images: which experimental parameters for the assessment of image quality?, Clement Fredembach, Geoff Woolfe, Jue Wang,CanonInformationSystemsResearchAustraliaPty.Ltd. (Australia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-21]

Examining the effect of task on viewing behavior in videos using saliency maps, Hani Alers, Judith A. Redi, Technische Univ. Delft (Netherlands);IngridHeynderickx,PhilipsResearch(Netherlands)[8291-29]

Spontaneous observer adjusted colors: color balance and salient objects in images,ToniVirtanen,Univ.ofHelsinki(Finland);AriSiren,NokiaCo.(Finland);MikkoKuhna,AaltoUniv.SchoolofScienceandTechnology(Finland);JaakkoAiraksinen,OlliOrenius,JenniRadun,Univ.ofHelsinki(Finland);MikkoNuutinen,AaltoUniv.SchoolofScienceandTechnology(Finland);TimoSäämänen,GöteNyman,Univ.ofHelsinki(Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-22]

SESSION 7B . . . . . . . . . . . . . . . . . . . . Wed. 3:50 to 4:10 pm


Session Chairs: Susan P. Farnand, Rochester Institute of Technology (United States)

Investigations of the tone reproduction curves on the perceived image quality for fine art reproductions, Jun Jiang, Franziska Frey, Susan Farnand, Rochester Institute of Technology (United States) . . . .[8293-23]

Characterizing eye movements during temporal- and global-quality assessment of h.264 compressed video sequences, Claire Mantel, NathalieGuyader,PatriciaLadret,GeluIonescu,Gipsa-lab(France);Thomas Kunlin, STMicroelectronics (France) . . . . . . . . . . . . . . . .[8291-30]

A compressed sensing model of crowding in peripheral vision, Jens Hocke,Univ.zuLübeck(Germany);MichaelDorr,SchepensEyeResearchInstitute(UnitedStates);ErhardtBarth,Univ.zuLübeck (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-31]

Foveated self-similarity in nonlocal image filtering, Alessandro Foi, TampereUniv.ofTechnology(Finland);GiacomoBoracchi,PolitecnicodiMilano (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-32]

A statistical study of the correlation between interest points and gaze points,MichaelNauge,Mohamed-ChakerLarabi,Univ.dePoitiers(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8291-33]

Interest point analysis as a model for the Poggendorrf illusion, Fred W. M.Stentiford,Univ.CollegeLondon(UnitedKingdom) . . . . . . . .[8291-34]

Conference8293



Image Quality in PrintSession Chair: Frans Gaykema, Océ Technologies B.V. (Netherlands)

A method of detecting changes in image quality via sensing on customer documents, Wencheng Wu, Beilei Xu, John Handley, Xerox Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-24]

Print quality analysis for ink-saving algorithms, Maria V. Ortiz Segovia, PurdueUniv.(UnitedStates)andOcéPrintLogicTechnologies(France);NicolasBonnier,OcéPrintLogicTechnologies(France);JanP.Allebach,Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-25]

Masking mediated print defect visibility predictor, Xiaochen Jing, PurdueUniv.(UnitedStates);HilaNachieli,DoronShaked,SmadarShiffman,Hewlett-PackardLabs.IsraelLtd.(Israel);JanP.Allebach,Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-26]

Psychophysical evaluation of banding visibility in the presence of print content,JiaZhang,PurdueUniv.(UnitedStates);DoronShaked,HilaNachlieli,SmadarShiffman,Hewlett-PackardLabs.IsraelLtd.(Israel);JanP. Allebach, Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . .[8293-27]


System Performance: VideoSession Chair: Luke C. Cui, LexmarkInternational,Inc.(UnitedStates)

No-reference video quality assessment of H.264 video streams based on semantic saliency maps, Hugo Boujut, Jenny Benois-Pineau, Toufik Ahmed,BordeauxUniv.(France);OferHadar,Ben-GurionUniv.oftheNegev(Israel);PatrickBonnet,AudematWorldcastSystems (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-28]

Linking quality assessment of free-viewpoint video objects up with algorithm development, Sara Kepplinger, Technische Univ. Ilmenau (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-29]

A perceptual optimization of H.264/AVC bit allocation at the frame and macroblock levels, Miryem Hrarti, Hakim Saadane, Mohamed-Chaker Larabi,XLIM-SIC(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-30]

QoE assessment method for mobile video services based on user motivation, Fumiya Kobayashi, Masataka Masuda, Takanori Hayashi, NTT NetworkInnovationLabs.(Japan) . . . . . . . . . . . . . . . . . . . . . . . . .[8293-31]

Quality rules for detection, recognition, and identification in video-surveillance applications,Mohamed-ChakerLarabi,DidierNicholson,Univ. de Poitiers (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-32]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 10 . . . . . . . . . . . . . . . . . . . Thurs. 2:00 to 3:20 pm

Image Quality Evaluation: New DevelopmentsSession Chair: Göte S. Nyman, Univ. of Helsinki (Finland)

A learning-based approach for automated quality assessment of computer-rendered images,XiZhang,GadyAgam,IllinoisInstituteofTechnology (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-33]

A comparison of techniques for superresolution evaluation, Monica A. Trifas, Jacksonville State Univ. (United States) . . . . . . . . . . . . . . .[8293-34]

Detection of image quality metamers based on the metric for unified image quality, Kimiyoshi Miyata, National Museum of Japanese History (Japan);NorimichiTsumura,ChibaUniv.(Japan) . . . . . . . . . . . . .[8293-35]

A new method to identify and quantify image distortion based on Gabor filter bank and multiple regression analysis, Benhur Ortiz Jaramillo, Univ. Nacional de Colombia (Colombia) and Univ. Gent (Belgium);JulioCesarGarciaAlvarez,Univ.NacionaldeColombia(Colombia);HartmutFühr,RWTHAachen(Germany);GermanCastellanosDominguez,Univ.NacionaldeColombia(Colombia);WilfriedPhilips,Univ.Gent (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-36]

Conference8293


Conference8294Monday-Wednesday 23-25 January 2012 • Proceedings of SPIE Vol. 8294

Visualization and Data Analysis 2012Conference Chairs: Pak Chung Wong, PacificNorthwestNationalLab.(UnitedStates);David L. Kao, NASAAmesResearchCtr.(UnitedStates);Ming C. Hao, Hewlett-PackardLabs.(UnitedStates);Chaomei Chen, Drexel Univ. (United States)

Conference Co-Chairs: Robert Kosara, TheUniv.ofNorthCarolinaatCharlotte(UnitedStates);Mark A. Livingston, U.S.NavalResearchLab.(UnitedStates);Jinah Park, KoreaAdvancedInstituteofScienceandTechnology(Korea,Republicof);Ian Roberts, PacificNorthwestNationalLab.(United States)

Program Committee: Madjid Allili, Bishop’sUniv.(Canada);Guoning Chen, TheUniv.ofUtah(UnitedStates);Yi-Jen Chiang, Polytechnic Institute of NYU(UnitedStates);George Chin, PacificNorthwestNationalLab.(UnitedStates);Scott E. Dillard, PacificNorthwestNationalLab.(UnitedStates);Marian Dörk, Univ.ofCalgary(Canada);Sussan Einakian, TheUniv.ofAlabamainHuntsville(UnitedStates);Matti T. Gröhn, Ctr. for Scientific Computing(Finland);Halldor Janetzko, Univ.Konstanz(Germany);Ming Jiang, LawrenceLivermoreNationalLab.(UnitedStates);Alark Joshi, Boise StateUniv.(UnitedStates);Dan Keefe, Univ.ofMinnesota(UnitedStates);Daniel A. Keim, Univ.Konstanz(Germany);Bongshin Lee, Microsoft Corp.(UnitedStates);Bob Lewis, WashingtonStateUniv.(UnitedStates);Guo-Shi Li, ExxonMobilUpstreamResearchCompany(UnitedStates);Peter Lindstrom, LawrenceLivermoreNationalLab.(UnitedStates);Lars Linsen, JacobsUniv.BremengGmbH(Germany);Zhanping Liu, Univ. of Pennsylvania(UnitedStates);Lucille T. Nowell, U.S.Dept.ofEnergy(UnitedStates);Harald Obermaier, Univ.ofKaiserslautern(Germany);Donald A. Pellegrino, Jr., DrexelUniv.(UnitedStates);William Pike, PacificNorthwestNationalLab.(UnitedStates);Theresa-Marie Rhyne, Computer GraphicsandE-Learning(UnitedStates);Tobias Schreck, Univ.Konstanz(Germany);Han-Wei Shen, TheOhioStateUniv.(UnitedStates);Chad A. Steed, OakRidgeNationalLab.(UnitedStates);Kalpathi R. Subramanian, TheUniv.ofNorthCarolinaatCharlotte(UnitedStates);Soon Tee Teoh, SanJoséStateUniv.(UnitedStates);Matthew O. Ward, WorcesterPolytechnicInstitute(UnitedStates);Yingcai Wu, Univ. of California, Davis (United States);Caixia Zhang, Google(UnitedStates);Jian Zhang, DrexelUniv.(UnitedStates);Song Zhang, Mississippi State Univ. (United States)

Cosponsored by

Monday 23 JanuaryOpening Remarks . . . . . . . . . . . . . . . .Mon. 8:30 to 8:45 am

Session Chair: Pak Chung Wong, PacificNorthwestNationalLab.(United States)

Information Visualization (IVS) Introduction . . . . . . . . . . . . . . . . . . . . Mon. 8:45 to 9:00 am

Chaomei Chen, Drexel Univ. (United States)

SESSION 1 . . . . . . . . . . . . . . . . . . . . .Mon. 9:00 to 10:00 am

Interactive VisualizationSession Chair: Pak Chung Wong, PacificNorthwestNationalLab.

(United States)

StreamSqueeze: a dynamic stream visualization for monitoring of event data,FlorianMansmann,MilosKrstajic,FabianFischer,EnricoBertini, Univ. Konstanz (Germany) . . . . . . . . . . . . . . . . . . . . . . . .[8294-01]

Interactive data-centric viewpoint selection, Han Suk Kim, Didem Unat, Scott B. Baden, Jurgen P. Schulze, Univ. of California, San Diego (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-02]

Interactive analysis of situational awareness metrics, Derek R. Overby, James A. Wall, John Keyser, Texas A&M Univ. (United States) . .[8294-03]

SESSION 2 . . . . . . . . . . . . . . . . . . . .Mon. 10:30 to 11:10 am

Visual AnalyticsSession Chair: Florian Mansmann, Univ. Konstanz (Germany)

Incremental visual text analytics of news story development, Milos Krstajic, Univ. Konstanz (Germany) . . . . . . . . . . . . . . . . . . . . . . . .[8294-04]

Guided text analysis using adaptive visual analytics, Chad A. Steed, ChristopherT.Symons,FrankA.DeNap,ThomasE.Potok,OakRidgeNationalLab.(UnitedStates). . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-05]


Visualization Techniques and ApplicationsSession Chair: Chad A. Steed, OakRidgeNationalLab.(UnitedStates)

Designing a better weather display, Colin Ware, Matthew Plumlee, The Univ. of New Hampshire (United States) . . . . . . . . . . . . . . . . . . . .[8294-06]

Visualization feedback for musical ensemble practice: a case study on phrase articulation and dynamics, Trevor Knight, Nicolas Boulliot, Jeremy Cooperstock, McGill Univ. (Canada) . . . . . . . . . . . . . . . .[8294-07]

Exploring ensemble visualization, Christopher G. Healey, Madhura N. Phadke,LiffordPinto,NorthCarolinaStateUniv.(UnitedStates);FemiAlabi, Jonathan M. Harter, Russell M. Taylor II, The Univ. of North Carolina atChapelHill(UnitedStates);XunleiWu,RenaissanceComputingInstitute(UnitedStates);HannahPetersen,SteffenA.Bass,DukeUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-08]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to1:50pm

Keynote Presentation I . . . . . . . . . Mon. 1:50 to 2:40 pmSession Chair: Mark A. Livingston, U.S.NavalResearchLab.(United

States)

Title TBD, Patrick Hanrahan, Stanford Univ. (United States) . [8294-42]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Mon. 3:00 to 3:40 pm

Large Data VisualizationSession Chair: Mark A. Livingston, U.S.NavalResearchLab.(United

States)

Parallel large-data visualization with display walls,LuizScheidegger,FacebookInc.(UnitedStates);HuyVo,PolytechnicInstituteofNewYorkUniv.(UnitedStates);JensKruger,Univ.desSaarlandes(Germany);ClaudioT.Silva,PolytechnicInstituteofNewYorkUniv.(UnitedStates);JoaoL.D.Comba,Univ.FederaldoRioGrandedoSul(Brazil) . .[8294-09]

Visual exploratory analysis of a large volume of SQL log data with the SDSS log viewer,JianZhang,ChaomeiChen,MichaelVogeley,DannyPan,DrexelUniv.(UnitedStates);AniThakar,JordanRaddick,TheJohnsHopkins Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-10]


SESSION 5 . . . . . . . . . . . . . . . . . . . . . Mon. 4:10 to 5:10 pm

EvaluationsSession Chair: Christopher G. Healey, North Carolina State Univ.

(United States)

Comparison of open-source visual analytics toolkits, John R. Harger, SandiaNationalLabs.(UnitedStates)andTheUniv.ofNewMexico(UnitedStates);PatriciaJ.Crossno,SandiaNationalLabs.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-11]

Evaluation of progressive treemaps to convey tree and node properties, René Rosenbaum, Bernd Hamann, Univ. of California, Davis (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-12]

Evaluation of multivariate visualizations: a case study of refinements and user experience,MarkA.Livingston,JonathanDecker,U.S.NavalResearchLab.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-13]


SESSION 6 . . . . . . . . . . . . . . . . . . . Tues. 10:00 to 10:40 am

Geo-Temporal VisualizationsSession Chair: Chaomei Chen, Drexel Univ. (United States)

Integrating sentiment analysis and term associations with geo-temporal visualizations on customer feedback streams, Ming C. Hao, Hewlett-PackardLabs.(UnitedStates);ChristianRohrdantz,HalldórJanetzko,DanielA.Keim,Univ.Konstanz(Germany);UmeshwarDayal,Hewlett-PackardLabs.(UnitedStates);Lars-ErikHaug,Hewlett-PackardCo.(UnitedStates);MeichunHsu,Hewlett-PackardLabs.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-14]

A self-adaptive technique for visualizing geospatial data in 3D with minimum occlusion, Abon Chaudhuri, Han-Wei Shen, The Ohio State Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-15]


Visualization AlgorithmsSession Chair: Han-Wei Shen, The Ohio State Univ. (United States)

Space/error tradeoffs for lossy wavelet reconstruction, Jonathan Frain, R. Daniel Bergeron, The Univ. of New Hampshire (United States) [8294-16]

A configurable data prefetching scheme for interactive visualization of large-scale volume data, Byungil Jeong, Paul Navratil, Kelly Gaither, Gregory Abram, Gregory P. Johnson, The Univ. of Texas at Austin (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-17]

A general approach for similarity-based linear projections using a genetic algorithm, James A. Mouradian, Bernd Hamann, René Rosenbaum, Univ. of California, Davis (United States) . . . . . . . . .[8294-18]

Image space adaptive volume rendering, Andrew Corcoran, John Dingliana, Trinity College Dublin (Ireland) . . . . . . . . . . . . . . . . . . .[8294-19]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

Keynote Presentation II . . . . . . . .Tues. 2:00 to 2:50 pmSession Chair: Ming C. Hao, Hewlett-PackardLabs.(UnitedStates)

Imaging the Antikythera Mechanism, Thomas Malzbender, Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . [8294-43]


Poster Fast Forward ISession Chair: Robert F. Erbacher, Utah State Univ. (United States)


conference.


Poster Fast Forward IISession Chair: Robert F. Erbacher, Utah State Univ. (United States)


conference.





X3DBio: a visual analysis tool for biomolecular structure exploration, HongYi,RenaissanceComputingInstitute(UnitedStates);AbhishekSingh, Yaroslava G. Yingling, North Carolina State Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-25]

Increasing the perceptual salience of relationships in parallel coordinate plots, Jonathan M. Harter, Xunlei Wu, The Univ. of North CarolinaatChapelHill(UnitedStates);DanielDougherty,MichiganStateUniv.(UnitedStates);HannahPetersen,SteffenBass,DukeUniv.(UnitedStates);RussellM.TaylorII,TheUniv.ofNorthCarolinaatChapelHill(UnitedStates);MadhuraN.Phadke,LiffordPinto,NorthCarolinaStateUniv.(UnitedStates);OluwafemiS.Alabi,TheUniv.ofNorthCarolinaatChapel Hill (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-26]

Comparative visualization of ensembles using ensemble surface slicing, Oluwafemi S. Alabi, The Univ. of North Carolina at Chapel Hill (UnitedStates);XunleiWu,RenaissanceComputingInstitute(UnitedStates);HannahPetersen,SteffenBass,DukeUniv.(UnitedStates);SharonZhong,MichiganStateUniv.(UnitedStates);MadhuraN.Phadke,LiffordPinto,ChristopherG.Healey,NorthCarolinaStateUniv.(UnitedStates);RussellM.TaylorII,TheUniv.ofNorthCarolinaatChapelHill(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-27]

Agglomerative clustering of small world graphs around nodes of interest, Fintan McGee, Trinity College Dublin (Ireland) . . . . . . . .[8294-28]

A performance assessment on the effectiveness of digital image registration methods,SteveT.Kacenjar,LockheedMartinCorp.(UnitedStates);BingLi,LockheedMartinSystemsIntegration-Owego(UnitedStates);AlanOstrow,LockheedMartinMaritimeSystems&Sensors(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-29]

An evaluation of rendering and interactive methods for volumetric data exploration in virtual reality environments, Nan Wang, Alexis Paljic, Philippe Fuchs, Mines ParisTech (France) . . . . . . . . . . . . . . . . . .[8294-30]

ProDV: a case study in delivering visual analytics, Derek R. Overby, Jim Wall, John Keyser, Texas A&M Univ. (United States) . . . . . . . . . .[8294-31]

Conference8294


Efficient, dynamic data visualization with persistent data structures, JosephA.Cottam,AndrewLumsdaine,IndianaUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-32]

Radial visualizations for comparative data analysis, Geoffrey Draper, MatthewG.Styles,BrighamYoungUniv.-Hawaii(UnitedStates);RichardF. Riesenfeld, Brigham Young Univ. (United States) . . . . . . . . . . .[8294-33]

Glyph visualization for temporal analysis of spatial sensor activity, Derek R. Overby, James A. Wall, John Keyser, Texas A&M Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-34]

uVis: a formula-based visualization tool,SorenLauesen,KostasPantazos, Mohammad A. Kuhail, Shangjin Xu, The IT Univ. of Copenhagen (Denmark) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-35]

Exploiting major trends in subject hierarchies for large-scale collection visualization, Charles-Antoine Julien, Pierre Tirilly, Univ. ofWisconsin-Milwaukee(UnitedStates);JohnE.Leide,CatherineGuastavino, McGill Univ. (Canada) . . . . . . . . . . . . . . . . . . . . . . . .[8294-36]

Visualization of multidimensional time,LutherA.Tychonievich,BrighamYoungUniv.(UnitedStates)andUniv.ofVirginia(UnitedStates);RobertP.Burton, Brigham Young Univ. (United States) . . . . . . . . . . . . . . . .[8294-37]

Degeneracy-aware interpolation of 3D diffusion tensor fields, Chongke Bi,ShigeoTakahashi,TheUniv.ofTokyo(Japan);IsseiFujishiro,KeioUniv. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-38]

Visualization and analysis of 3D gene expression patterns in zebrafish using web services,DomePotikanond,FonsJ.Verbeek,LeidenUniv.(Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-39]

Vortex core detection: back to basics, Allen Van Gelder, Univ. of California, Santa Cruz (United States) . . . . . . . . . . . . . . . . . . . . . .[8294-40]

Multiscale graph Laplacian analysis for volumetric datasets based on anisotropic heat diffusion,ShuaiLi,HongQin,StonyBrookUniv.(UnitedStates);AiminHao,BeiHangUniv.(China) . . . . . . . . . . . . . . . . . .[8294-41]


SESSION 10 . . . . . . . . . . . . . . . . . . . .Wed. 9:50 to 10:30 am

Bioinformatics VisualizationsSession Chair: Mark A. Livingston, U.S.NavalResearchLab.(United

States)

Visualization of mappings between the gene ontology and cluster trees,AndreasKerren,IlirJusufi,VladyslavAleksakhin,LinnaeusUniv.(Sweden);FalkSchreiber,LeibnizInstituteofPlantGeneticsandCropPlantResearch(Germany)andMartin-LutherUniv.Halle-Wittenberg(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-20]

Visualizing uncertainty in biological expression data, Clemens Holzhüter,Univ.Rostock(Germany);AlexanderLex,DieterSchmalstieg,Hans-JörgSchulz,TechnischeUniv.Graz(Austria);HeidrunSchumann,Univ.Rostock(Germany);MarcStreit,TechnischeUniv.Graz (Austria) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8294-21]


Flow VisualizationSession Chair: David L. Kao, NASA Ames Research Ctr. (United

States)

Instant visitation maps for interactive visualization of uncertain particle trajectories, Kai Bürger, Roland Fraedrich, Technische Univ. München(Germany);DoritMerhof,Univ.Konstanz(Germany);RüdigerWestermann, Technische Univ. München (Germany) . . . . . . . . . .[8294-22]

Motion visualization in large particle simulations, Roland Fraedrich, Rüdiger Westermann, Technische Univ. München (Germany) . . .[8294-23]

Animating streamlines with repeated asymmetric patterns for steady flow visualization,Chih-KuoYeh,NationalChengKungUniv.(Taiwan);ZhanpingLiu,Univ.ofPennsylvania(UnitedStates);Tong-YeeLee,National Cheng Kung Univ. (Taiwan) . . . . . . . . . . . . . . . . . . . . . . .[8294-24]

Closing Remarks . . . . . . . . . . . . . . Wed. 12:00 to 12:15 pmSession Chair: David L. Kao, NASA Ames Research Ctr. (United

States)

Conference8294


Conference8295AMonday-Wednesday 23-25 January 2012 • Proceedings of SPIE Vol. 8295A

Image Processing: Algorithms and Systems XConference Chairs: Karen O. Egiazarian, TampereUniv.ofTechnology(Finland);Sos S. Agaian, TheUniv.ofTexasatSanAntonio(UnitedStates);Atanas P. Gotchev, Tampere Univ. of Technology (Finland)

Program Committee: Til Aach, RWTHAachen(Germany);Gözde Bozdagi Akar, MiddleEastTechnicalUniv.(Turkey);Junior Barrera, Univ. de São Paulo(Brazil);Jenny Benois-Pineau, BordeauxUniv.(France);Reiner Creutzburg, FachhochschuleBrandenburg(Germany);Paul Gader, Univ. ofFlorida(UnitedStates);John C. Handley, XeroxCorp.(UnitedStates);Vladimir Vasilyevich Lukin, NationalAerospaceUniv.(Ukraine);Stephen Marshall, Univ.ofStrathclyde(UnitedKingdom);Alessandro Neri, Univ.degliStudidiRomaTre(Italy);Françoise Prêteux, MinesParisTech(France);Gianni Ramponi, Univ.degliStudidiTrieste(Italy);Jagath K. Samarabandu, TheUniv.ofWesternOntario(Canada);Ivan W. Selesnick, Polytechnic InstituteofNYU(UnitedStates);Damir Sersic, Univ.ofZagreb(Croatia);Akira Taguchi, Musashi Kogyo Univ. (Japan)

Monday 23 JanuarySESSION 1 . . . . . . . . . . . . . . . . . . . . .Mon. 8:50 to 10:10 am

Image AnalysisSession Chair: Atanas P. Gotchev, Tampere Univ. of Technology

(Finland)

Analysis of different image-based biofeedback models for improving cycling performances, Daniele Bibbo, Silvia Conforto, Ivan Bernabucci, Marco Carli, Maurizio Schmid, Tommaso D’Alessio, Univ. degli Studi di Roma Tre (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-01]

Textured areas detection and segmentation in circular harmonic functions domain,LucaCostantini,LiciaCapodiferro,FondazioneUgoBordoni(Italy);MarcoCarli,AlessandroNeri,Univ.degliStudidiRomaTre(Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-02]

Searching for streamer trajectories on synoptic maps of the sun corona,AntoineLlebaria,ObservatoireAstronomiquedeMarseille-Provence (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-03]

Performance evaluation for 2D and 3D filtering methods of noise removal in color images,VladimirVasilyevichLukin,AlexanderA.Zelensky,NikolayN.Ponomarenko,NationalAerospaceUniv.(Ukraine);KarenO.Egiazarian,JaakkoT.Astola,TampereUniv.ofTechnology(Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-04]


Image Classification and RecognitionSession Chair: Sos S. Agaian, The Univ. of Texas at San Antonio

(United States)

Integrated text detection and recognition in natural images, Nadejda S. Roubtsova,TechnischeUniv.Eindhoven(Netherlands)andViNotionB.V.(Netherlands);RobWijnhoven,ViNotionB.V.(Netherlands)andTechnischeUniv.Eindhoven(Netherlands);PeterH.N.deWith,TechnischeUniv.Eindhoven(Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-05]

Ear recognition based on edge potential function, Federica Battisti, MarcoCarli,Univ.degliStudidiRomaTre(Italy);FrancescoG.B.DeNatale,Univ.degliStudidiTrento(Italy);AlessandroNeri,Univ.degliStudidi Roma Tre (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-06]

Feature extraction from ladar data using modified GPCA, Peter F. Stiller, Texas A&M Univ. (United States) . . . . . . . . . . . . . . . . . . [8295A-07]

Recognition of rotated images using the multi-valued neuron and rotation-invariant 2D Fourier descriptors,EvgeniAizenberg,IrvingJ.Bigio,EladioRodriguez-Diaz,BostonUniv.(UnitedStates) . . . [8295A-08]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:20 pm

Image Representation ISession Chair: Karen O. Egiazarian, Tampere Univ. of Technology

(Finland)

A graph representation of the topology of color images, Peter Saveliev, Marshall Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-09]

Amoeba-based superpixel partitioning of multispectral images into elementary, uniform, connected units,JacopoGrazzini,LakshmanPrasad,LosAlamosNationalLab.(UnitedStates) . . . . . . . . . . [8295A-10]

Smooth partition of unity with Hermite interpolation: applications to image processing,LubomirT.Dechevsky,PeterZanaty,ArneLakså,Børre Bang, Narvik Univ. College (Norway) . . . . . . . . . . . . . . . [8295A-11]

An algorithm for GPGPU-computing of multidimensional DWTs based on bijective mapping of tensor-product wavelet bases of different number of variables,LubomirT.Dechevsky,JosteinBratlie,BørreBang,ArneLakså,NarvikUniv.College(Norway) . . . . . . . . . . . . . . . . [8295A-12]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Mon. 4:00 to 5:00 pm

Image Representation IISession Chair: Karen O. Egiazarian, Tampere Univ. of Technology

(Finland)

Quantitative evaluation of image mosaicing in multiple scene categories, Debabrata Ghosh, Sangho Park, Naima Kaabouch, William Semke, Ronald Fevig, The Univ. of North Dakota (United States)[8295A-13]

Curvelet transform with adaptive tiling,HasanAl-Marzouqi,GhassanAl-Regib, Georgia Institute of Technology (United States) . . . . [8295A-14]

Tetrachromatic colour space,AlfredoRestrepo,Univ.deLosAndes(Colombia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-15]




Image Synthesis and Reconstruction ISession Chair: Karen O. Egiazarian, Tampere Univ. of Technology

(Finland)

Smooth image inpainting by least square oriented edge prediction, EmilianoPallotti,LiciaCapodiferro,FedericaMangiatordi,FondazioneUgoBordoni(Italy);PaoloSità,Univ.degliStudidiRomaTre(Italy) [8295A-16]

Image inpainting using cubic spline-based edge reconstruction, Viatcheslav Voronin, Vladimir I. Marchuk, South-Russian State Univ. ofEconomicsandService(RussianFederation);KarenO.Egiazarian,TampereUniv.ofTechnology(Finland);AlexandrSherstobitov,South-RussianStateUniv.ofEconomicsandService(Russian Federation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-17]

Global registration and stabilization of jittered and noisy airborne image sequences, Nader M. Namazi, The Catholic Univ. of America (UnitedStates);WilliamScharpf,U.S.NavalResearchLab.(UnitedStates);JeromeObermark,DCSCorp.(UnitedStates);JamesCaron,ResearchSupport Instruments, Inc. (United States) . . . . . . . . . . . . . . . . . [8295A-18]


Image Synthesis and Reconstruction IISession Chair: Karen O. Egiazarian, Tampere Univ. of Technology

(Finland)

Image and video restoration via Ising-like models, Ofer Hadar, Ben-GurionUniv.oftheNegev(Israel);EliahuCohen,TelAvivUniv. (Israel) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-19]

Region adaptive correction method for radial distortion of fish-eye image, Ki Sun Song, Young Seok Han, Moon Gi Kang, Yonsei Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-20]

Super-resolution image reconstruction with edge adaptive weight in video sequence, Ji Yong Kwon, Du Sic Yoo, Moon Gi Kang, Yonsei Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-21]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm


Image Filtering and Enhancement ISession Chair: Atanas P. Gotchev, Tampere Univ. of Technology

(Finland)

Color image enhancement based on genetic algorithm and ensemble empirical mode decomposition, Somayeh Bakhtiari, Sos Agaian, Mo Jamshidi, The Univ. of Texas at San Antonio (United States) . . [8295A-22]

Image classification and interpolation,AnimeshKhemka,KLA-TencorCorp.(UnitedStates);CharlesA.Bouman,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-23]

Optimal fractional filter for image segmentation, Amir Nakib, Yohanna SchulzeM.D.,EricPetit,Univ.Paris12-ValdeMarne(France) [8295A-24]

Multi-scale image enhancement using a second derivative-like measure of contrast, Shahan C. Nercessian, Karen Panetta, Tufts Univ. (UnitedStates);SosAgaian,TheUniv.ofTexasatSanAntonio(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-25]


Image Filtering and Enhancement IISession Chair: Atanas P. Gotchev, Tampere Univ. of Technology

(Finland)

A new denoising method in high-dimensional PCA space, Quoc Bao Do, Univ. Paris 13 (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-26]

Intelligent detection of impulse noise using multilayer neural network with multi-valued neurons, Igor Aizenberg, Glen Wallace, Texas A&M Univ.-Texarkana (United States) . . . . . . . . . . . . . . . . . . . . . . . . [8295A-27]

An homomorphic filtering and expectation maximization approach for the point spread function estimation in ultrasound imaging, Said Benameur,EiffelMedtech,Inc.(Canada);MaxMignotte,Univ.deMontréal(Canada);FredericLavoie,EiffelMedtech,Inc.(Canada) . . . . . [8295A-28]





Intensity-constrained, flat-kernel filter for local dark feature suppression: application to removal of hair artifacts in dermatoscopic images,AlexA.Gutenev,RetiariusPtyLtd.(Australia) . . . . . . [8295A-35]

New decision support tool for acute lymphoblastic leukemia classification, Monica Madhukar, Sos Agaian, Anthony Chronopoulos, The Univ. of Texas at San Antonio (United States) . . . . . . . . . . [8295A-36]

Sharpness metric for no-reference image visual quality assessment, VladimirVasilyevichLukin,NikolayN.Ponomarenko,OlegEremeev,NationalAerospaceUniv.(Ukraine);KarenO.Egiazarian,JaakkoAstola,Tampere Univ. of Technology (Finland) . . . . . . . . . . . . . . . . . . . [8295A-37]

A new system of computer-aided diagnosis of skin lesions, Isaac A. Sanchez, Sos Agaian, The Univ. of Texas at San Antonio (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-38]

Image denoising using a combined criterion,EvgenySemenishchev,VladimirI.Marchuk,South-RussianStateUniv.ofEconomicsandService(RussianFederation);KarenO.Egiazarian,TampereUniv.ofTechnology(Finland);ViatcheslavVoronin,South-RussianStateUniv.ofEconomicsand Service (Russian Federation) . . . . . . . . . . . . . . . . . . . . . . . [8295A-39]

Non-cooperative stationary ground targets detection based on IRST, DeguiYang,YuliangQin,XufengZhang,XizhangWei,HongqiangWang,National Univ. of Defense Technology (China) . . . . . . . . . . . . . [8295A-40]

Motion-compensated spatial-temporal filtering for noisy color filter array sequence,MinSeokLee,YonseiUniv.(Korea,Republicof) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-41]

Application of 1D FIR filter methods to 3D polygonal meshes, William S. Ward, The Univ. of Texas at San Antonio (United States) . . [8295A-42]

An automatic approach for 3D registration of CT scans, Yang Hu, EliSaber,SohailDianat,SreenathRaoVantaram,RochesterInstituteofTechnology(UnitedStates);VishwasAbhyankar,DataPhysicsResearch,Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-43]

Boundary handling mechanism for lifting-based spatial adaptation of filter banks, Dakala Jayachandra, Anamitra Makur, Nanyang Technological Univ. (Singapore) . . . . . . . . . . . . . . . . . . . . . . . . [8295A-44]

Conference8295A


A simple and efficient algorithm for connected-component labeling in color images,M.EmreCelebi,LouisianaStateUniv.Shreveport(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-45]

An adaptive and deterministic method for initializing the Lloyd-Max algorithm,JaredVicory,M.EmreCelebi,LouisianaStateUniv.Shreveport(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-46]

Multi-resolution analysis for region of interest extraction in thermographic, nondestructive evaluation, Benhur Ortiz Jaramillo, Univ.NacionaldeColombia(Colombia);HernanDaríoBenitezRestrepo,PontificiaUniv.Javeriana,Cali(Colombia);GermanCastellanosDominguez,Univ.NacionaldeColombia(Colombia);WilfriedPhilips,Univ.Gent (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-47]

Estimation of deformations in ultrasound images using dynamic programming,SérgioS.Furuie,FernandoM.Cardoso,EscolaPolitécnicada Univ. de São Paulo (Brazil) . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-48]

Combining skin texture and facial structure for face identification, RachelE.Manoni,PhotonResearchAssociates,Inc.(UnitedStates);RoxanneL.Canosa,RochesterInstituteofTechnology(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-49]

Development of a human vision simulation camera and its application, Hiroshi Okumura, Mai Fukusaki, Shoichiro Takubo, Kohei Arai, Saga Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-50]

Reconstruction from divergent ray projections, Challa Subrahmanya Sastry,InternationalInstituteofInformationTechnology(India);SantoshSingh,SiemensInformationSystemsLtd.(India) . . . . . . . . . . . [8295A-51]


SESSION 9 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Image Processing Systems ISession Chair: Sos S. Agaian, The Univ. of Texas at San Antonio

(United States)

Hybrid gesture recognition system for short-range use, Akihiro Minagawa,FujitsuLabs.(Japan);WeiFan,FujitsuResearchandDevelopmentCenterCo.,Ltd.(China);YutakaKatsuyama,HiroakiTakebe,NoriakiOzawa,YoshinobuHotta,FujitsuLabs.(Japan);JunSun,FujitsuResearchandDevelopmentCenterCo.,Ltd.(China) . . . . . . . . [8295A-29]

Tracking white road line by particle filter from the video sequence acquired by the camera attached to a walking human body, Shohei Takahashi, Jun Ohya, Waseda Univ. (Japan) . . . . . . . . . . . . . . [8295A-30]

Driver/passenger discrimination for the interaction with the dual-view touch screen integrated to the automobile centre consol, Andrey Makrushin,EnricoHerrmann,JanaDittmann,Otto-von-Guericke-Univ.Magdeburg(Germany);ClausVielhauer,FachhochschuleBrandenburg(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-31]

Conference8295A


Image Processing Systems IISession Chair: Sos S. Agaian, The Univ. of Texas at San Antonio

(United States)

A linear filter design technique for equalizing document scanners, AhmedHamadEid,LexmarkInternational,Inc.(UnitedStates) [8295A-32]

Application of spatial contrast techniques on satellite imagery for cloud shape differentiation, Jules R. Dim, Hiroshi Murakami, Japan AerospaceExplorationAgency(Japan) . . . . . . . . . . . . . . . . . . [8295A-33]

A multi-step system for screening and localization of hard exudates in retinal images, Ajit S. Bopardikar, Vishal Bhola, Raghavendra B. S., RangavittalNarayanan,SamsungElectronics,IndiaSoftwareOperationsLtd.(India) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295A-34]


Conference8295BMonday-Tuesday 23-24 January 2012 • Proceedings of SPIE Vol. 8295B

Parallel Processing for Imaging Applications IIConference Chairs: John Recker, Hewlett-PackardLabs.(UnitedStates);Guijin Wang, Tsinghua Univ. (China)

Program Committee: Jiansheng Chen, TsinghuaUniv.(China);Justin Hensley, AdvancedMicroDevices,Inc.(UnitedStates);Wen-Mei Hwu, Univ. ofIllinoisatUrbana-Champaign(UnitedStates);Constantine Kreatsoulas, Merck&Co.,Inc.(UnitedStates);I-Jong Lin, Hewlett-PackardLabs.(UnitedStates);Thomas Malzbender, Hewlett-PackardLabs.(UnitedStates);Richard J. Moore, 3MCo.(UnitedStates);Sung W. Park, Samsung ElectronicsCo.,Ltd.(Korea,Republicof);William Pratt, Pixelsoft,Inc(UnitedStates);Norman Rubin, AMD(UnitedStates);Huachun Tan, Beijing InstituteofTechnology(China);Chung M. Wong, Northrop Grumman Aerospace Systems (United States)

Monday 23 JanuarySESSION 11 . . . . . . . . . . . . . . . Mon. 10:40 am to 12:10 pm

Parallel SystemsSession Chair: William Pratt, PixelSoft, Inc. (United States)

GPGPU-based surface inspection from structured white light (Invited Paper),MiguelBordalloLopez,Univ.ofOulu(Finland);KarriNiemelä,VTTTechnicalResearchCtr.ofFinland(Finland);OlliJohannesSilvén,Univ.ofOulu (Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-52]

Real-time image stitching from streaming video, Jaco Cronje, Council for Scientific and Industrial Research (South Africa) and Univ. of Johannesburg(SouthAfrica);JasonDeVilliers,CouncilforScientificandIndustrial Research (South Africa) . . . . . . . . . . . . . . . . . . . . . . . [8295B-53]

IMPAIR-GPU: massively parallel deconvolution algorithm for GPUs, Michael Sherry, Andrew Shearer, National Univ. of Ireland, Galway (Ireland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-54]

Parallel processing architectures for H.264 deblocking filter on multicore platforms, Durga P. Prasad, Sekar Sonachalam, Mangesh Kumar Kunchamwar, Nageswara Rao Gunupudi, Parallel Prisms (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-55]

Keynote Presentation . . . . . . . . Mon. 12:10 to 12:40 pmSession Chair: William Pratt, Pixel Soft, Inc. (United States)

Compute infrastructure challenges of commercial digital print, I-JongLin,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . [8295B-56]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:40to2:00pm

SESSION 12 . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:30 pm

Parallel AlgorithmsSession Chair: Robert A. Ulichney, Hewlett-Packard Co. (United

States)

Interactive plenoptic rendering with GPUs,AndrewLumsdaine,GeorgiN.Chunev,IndianaUniv.(UnitedStates);TodorG.Georgiev,AdobeSystems Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-57]

Three-level GPU accelerated Gaussian mixture model for background subtraction,YinLi,GuijinWang,XinggangLin,TsinghuaUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-58]

Plane-dependent error diffusion on a GPU,YaoZhang,Univ.ofCalifornia,Davis(UnitedStates);JohnL.Recker,Hewlett-PackardLabs.(UnitedStates);RobertUlichney,IngeborgTastl,Hewlett-PackardCo.(UnitedStates);JohnD.Owens,Univ.ofCalifornia,Davis(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-59]

An analysis of OpenCL for portable imaging (Invited Paper), Richard J. Moore,3MCo.(UnitedStates);BenZimmer,3MCo.(UnitedStates)andUniv.ofWisconsin-EauClaire(UnitedStates) . . . . . . . . . . . . . [8295B-60]






Speed-up on GPU in Bayesian image reconstruction, Shuma Horiuchi, ShuheiYoshida,ZentaUshiyama,ManabuYamamoto,TokyoUniv.ofScience (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8295B-61]



Conference8296Sunday-Thursday 22-26 January 2012 • Proceedings of SPIE Vol. 8296

Computational Imaging XConference Chairs: Charles A. Bouman, PurdueUniv.(UnitedStates);Ilya Pollak, PurdueUniv.(UnitedStates);Patrick J. Wolfe, Harvard Univ. (United States)

Program Committee: Samit Basu, GESecurity(UnitedStates);Thomas S. Denney, Jr., AuburnUniv.(UnitedStates);Maya R. Gupta, Univ. of Washington(UnitedStates);Eric L. Miller, TuftsUniv.(UnitedStates);Joseph A. O’Sullivan, WashingtonUniv.inSt.Louis(UnitedStates);Zygmunt Pizlo, PurdueUniv.(UnitedStates);Stanley J. Reeves, AuburnUniv.(UnitedStates);Yongyi Yang, Illinois Institute of Technology (United States)

The 8296 Advance Program is not yet available. Please check the website for updated information: www.spie.org/ei112



Document Recognition and Retrieval XIXConference Chairs: Christian Viard-Gaudin, Univ.deNantes(France);Richard Zanibbi, Rochester Institute of Technology (United States)

Program Committee: Gady Agam, IllinoisInstituteofTechnology(UnitedStates);Elisa H. Barney Smith, BoiseStateUniv.(UnitedStates);Bill Barrett, BrighamYoungUniv.(UnitedStates);Kathrin Berkner, RicohInnovations,Inc.(UnitedStates);Bertrand Coüasnon, Institut National des SciencesAppliquéesdeRennes(France);Hervé Déjean, XeroxResearchCtr.EuropeGrenoble(France);Xiaoqing Ding, TsinghuaUniv.(China);David Scott Doermann, Univ.ofMaryland,CollegePark(UnitedStates);Oleg D. Golubitsky, GoogleWaterloo(Canada);Jianying Hu, IBM TJ WatsonResearchCtr.(UnitedStates);Laurence Likforman-Sulem, TelecomParisTech(France);Xiaofan Lin, Vobile,Inc.(UnitedStates);Marcus Liwicki, DeutschesForschungszentrumfürKünstlicheIntelligenzGmbH(Germany);Daniel P. Lopresti, LehighUniv.(UnitedStates);Hiroshi Sako, HoseiUniv.(Japan);Sargur N. Srihari, Univ.atBuffalo(UnitedStates);Venkata Subramaniam, IBMIndiaResearchLab.(India);Kazem Taghva, Univ.ofNevada,LasVegas(UnitedStates);George R. Thoma, NationalLibraryofMedicine(UnitedStates);Berrin Yanikoglu, Sabanci Univ. (Turkey);Jie Zou, NationalLibraryofMedicine(UnitedStates)






Bleed-through removal in degraded documents,RóisínF.Rowley-Brooke, Anil Kokaram, Trinity College Dublin (Ireland) . . . . . . . . .[8297-28]

Clustering document fragments using background color and texture information, Sukalpa Chanda, Katrin Franke, Gjøvik Univ. College (Norway);UmapadaPal,IndianStatisticalInstitute(India) . . . . . .[8297-29]

Lecture video segmentation and indexing, Di Ma, Gady Agam, Illinois Institute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8297-30]

Unsupervised categorization method of graphemes on handwritten manuscripts: application to style recognition, Hani Daher, Djamel Gaceb,VeroniqueEglin,StephaneBres,NicoleVincent,InstitutNationaldesSciencesAppliquéesdeLyon(France) . . . . . . . . . . . . . . . . .[8297-31]

Retrieving handwriting by combining word spotting and manifold ranking,SebastianPeñaSaldarriaga,Synchromedia(Canada);EmmanuelMorin, Christian Viard-Gaudin, Univ. de Nantes (France) . . . . . . .[8297-32]

The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition,FarèsMenasri,JérômeLouradour,Anne-LaureBianne-Bernard, Christopher Kermorvant, A2iA SA (France) . . . .[8297-33]

Using connected component decomposition to detect straight line segments in documents, Xiaofan Feng, Abdou Youssef, The George Washington Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . .[8297-34]

A synthetic document image dataset for developing and evaluating historical document processing methods, Daniel D. Walker IV, William B.Lund,EricK.Ringger,BrighamYoungUniv.(UnitedStates) . .[8297-35]


SESSION 1 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Invited Presentation ISession Chair: Christian Viard-Gaudin, Univ. de Nantes (France)

Large scale visual semantic extraction (Invited Paper), Samy Bengio, Google Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-01]


Region LabelingGraphical image classification using a hybrid of evolutionary algorithm and binary particle swarm optimization, Beibei Cheng, Missouri Univ. ofScienceandTechnology(UnitedStates);SameerK.Antani,NationalLibraryofMedicine(UnitedStates);R.JoeStanley,MissouriUniv.ofScienceandTechnology(UnitedStates);GeorgeThoma,NationalLibraryof Medicine (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-02]

Combining SVM classifiers to identify investigator name zones in biomedical articles,JongwooKim,DanielX.Le,GeorgeR.Thoma,NationalLibraryofMedicine(UnitedStates) . . . . . . . . . . . . . . . . .[8297-03]

Comprehensive color segmentation system for noisy digitized documents to enhance text extraction,AsmaOuji,YannLeydier,FrankLeBourgeois,InstitutNationaldesSciencesAppliquéesdeLyon (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-04]

Ensemble methods with simple features for document zone classification,TayoObafemi-Ajayi,GadyAgam,BingqingXie,IllinoisInstitute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8297-05]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to1:50pm


SESSION 3 . . . . . . . . . . . . . . . . . . . . . Wed. 1:50 to 3:30 pm

Handwriting RecognitionA robust omnifont open-vocabulary arabic OCR system using pseudo-2D-HMM,AbdullahM.Rashwan,CairoUniv.(Egypt)andRDI(Egypt);Mohsen A. Rashwan, Sherif Abdou, Ahmed Abdel-Hameed, Cairo Univ. (Egypt) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-06]

Variable length and context-dependent HMM letter form models for Arabic handwritten word recognition,Anne-LaureBianne-Bernard,A2iASA(France)andTelecomParisTech(France);FarèsMenasri,A2iASA(France);LaurenceLikforman-Sulem,TelecomParisTech(France);ChaficMokbel,Univ.ofBalamand(Lebanon);ChristopherKermorvant,A2iASA(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-07]

Post-processing for offline Chinese handwritten character string recognition,YanweiWang,XiaoqingDing,ChangsongLiu,TsinghuaUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-08]

Complexity reduction with recognition rate maintained for on-line handwritten Japanese text recognition, Jinfeng Gao, Tokyo Univ. Agriculture and Technology (Japan) . . . . . . . . . . . . . . . . . . . . . . .[8297-09]

Improving isolated and in-context classication of handwritten characters, Vadim Mazalov, Stephen M. Watt, The Univ. of Western Ontario (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-10]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pm

Graphics RecognitionUsing specific evaluation for comparing and combining competing algorithms: applying it to table column detection, Ana Costa C. Silva, Univ. do Porto (Portugal) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-11]

Identification of embedded mathematical formulas in PDF documents using SVM,XiaoyanLin,LiangcaiGao,ZhiTang,PekingUniv.(China);XuanHu,BeiHangUniv.(China);XiaofanLin,Vobile,Inc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-12]

Chemical structure recognition: a rule-based approach, Noureddin M. Sadawi, Alan P. Sexton, Volker Sorge, The Univ. of Birmingham (United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-13]

Quantify spatial relations to discover handwritten graphical symbols, JinpengLi,HaroldMouchère,ChristianViard-Gaudin,Univ.deNantes(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-14]

Thursday 26 JanuarySESSION 5 . . . . . . . . . . . . . . . . . . . . Thurs. 8:30 to 9:30 am

Invited Presentation IISession Chair: Richard Zanibbi, Rochester Institute of Technology

(United States)

Language modeling for information retrieval (Invited Paper), Christopher Manning, Stanford Univ. (United States) . . . . . . . . . . . . . . . . . . . .[8297-15]

SESSION 6 . . . . . . . . . . . . . . . . . . . Thurs. 9:30 to 10:10 am

Information RetrievalAutomatic indexing of scanned documents: a layout-based approach, DanielEsser,DanielSchuster,KlemensMuthmann,AlexanderSchill,Technische Univ. Dresden (Germany) . . . . . . . . . . . . . . . . . . . . . .[8297-16]

Layout-based substitution tree indexing and retrieval for mathematical expressions,ThomasSchellenberg,RichardZanibbi,BoYuan,RochesterInstitute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8297-17]


Human-Computer InteractionEfficient cost-sensitive human-machine collaboration for off-line signature verification,JohannesCoetzer,JacquesSwanepoel,StellenboschUniv.(SouthAfrica);RobertSabourin,EcoledeTechnologieSupérieure (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-18]

Questioned document workflow for handwriting with automated tools, Sargur N. Srihari, Krishnanand Das, Harish Srinivasan, Univ. at Buffalo (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-19]

Iterative analysis of document collections enables efficient human-initiated interaction, Joseph Chazalon, Bertrand Coüasnon, Institut NationaldesSciencesAppliquéesdeRennes(France) . . . . . . . .[8297-20]

VeriClick: an efficient tool for table format verification, George Nagy, Mangesh Tamhankar, Rensselaer Polytechnic Institute (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-21]

Asymptotic cost in document conversion, Dorothea Blostein, Queen’s Univ.(Canada);GeorgeNagy,RensselaerPolytechnicInstitute(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-22]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to1:50pm


Style or Writer IdentificationStyle comparisons in calligraphy, George Nagy, Rensselaer Polytechnic Institute(UnitedStates);ZiafenZhang,ShanghaiMaritimeInstitute (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-23]

An Oracle-based co-training framework for writer identification in offline handwriting,UtkarshPorwal,Univ.atBuffalo(UnitedStates);SreerangaRajan,FujitsuLabs.ofAmerica,Inc.(UnitedStates);VenuGovindaraju, Univ. at Buffalo (United States) . . . . . . . . . . . . . . . .[8297-24]

Handwritten document age classification based on handwriting styles, Chetan Ramaiah, Gaurav Kumar, Venu Govindaraju, Univ. at Buffalo (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-25]

Handwriting individualization using distance and rarity, Yi Tang, Sargur N.Srihari,Univ.atBuffalo(UnitedStates);HarishSrinivasan,JanyaInc.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-26]

Construction of language models for an handwritten mail reading system,OlivierMorillot,LaurenceLikforman-Sulem,TelecomParisTech(France);EmmanuèleGrosicki,DirectionGénéraledeL’armement (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8297-27]

Conference8297



Sensors, Cameras, and Systems for Industrial/Scientific Applications XIIIConference Chairs: Ralf Widenhorn, PortlandStateUniv.(UnitedStates);Valérie Nguyen, CEALetiMINATEC(France);Antoine Dupret, École Supérieured’IngénieursenElectroniqueetElectrotechnique(France)

Program Committee: Morley M. Blouke, PortlandStateUniv.(UnitedStates);Erik Bodegom, PortlandStateUniv.(UnitedStates);Glenn H. Chapman, SimonFraserUniv.(Canada);James A. DiBella, Sr., EastmanKodakCo.(UnitedStates);Terrence S. Lomheim, The Aerospace Corp. (UnitedStates);Pierre Magnan, InstitutSupérieurdel’Aéronautiqueetdel’Espace(France);Kevin J. Matherson, Hewlett-Packard Co. (United States);Alice L. Reinheimer, e2v(UnitedStates);Nobukazu Teranishi, PanasonicCorp.(Japan);Xinyang Wang, CMOSIS nv (Belgium)






Analysis of DC control of double-inlet pulse tube refrigerators for detectors,BingyanDu,LuoyangOptoelectronicDevelopmentCtr.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-26]

The embedded network infrared video monitoring system based on Linux OS,LeiLiu,NanjingUniv.ofScience&Technology(China);NingChen,NanjingNormalUniv.(China);XiaojunZhou,TaoPan,NanjingUniv.of Science & Technology (China) . . . . . . . . . . . . . . . . . . . . . . . . .[8298-27]

Motion blur-free time-of-flight range sensor,SeungkyuLee,ByongminKang, James D.K. Kim, Chang Yeong Kim, Samsung Advanced Institute of Technology (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-28]

CMOS buried double junction (BDJ) photodiode for trichromatic sensing,LienTu,SwetadriVasanSetlurNagesh,Univ.atBuffalo(UnitedStates);ZhenHongFu,OmniVisionTechnologies,Inc.(UnitedStates);Albert H. Titus, Univ. at Buffalo (United States) . . . . . . . . . . . . . .[8298-29]

On image sensor dynamic range utilized by security cameras, Anders Johannesson, Axis Communications AB (Sweden) . . . . . . . . . . .[8298-30]

Design of low-noise output amplifier for p-channel: fully depleted charge-coupled devices,SufiaHaque,StephenE.Holland,ArminKarcher,WilliamKolbe,NatalieRoe,LawrenceBerkeleyNationalLab.(UnitedStates);RobertGroulx,RaymondFrost,FrancoisDion,TeledyneDALSASemiconductor(Canada);GuobinWang,LawrenceBerkeleyNationalLab.(UnitedStates). . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-31]

S/N improvement for the optical-multiplex image-acquisition system, Tadakuni Narabu, Sony Corp. (Japan) . . . . . . . . . . . . . . . . . . . . .[8298-32]


SESSION 1 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

High Speed SensorsSession Chair: Morley M. Blouke, Portland State Univ. (United States)

High-speed VGA resolution CMOS image sensor with global shutter, Pieter Willems, Guido Vanhorebeek, Cheng Ma, CMOSIS nv (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-01]

High-speed global shutter CMOS machine vision sensor with high-dynamic range image acquisition and embedded intelligence, Ángel B.Rodríguez-Vázquez,Univ.deSevilla(Spain);RafaelDominguez-Castro,Fernando Medeiro, Francisco Jimenez-Garrido, Anafocus (Spain)[8298-02]

High-speed CMOS image sensor for high-throughput lensless microfluidic imaging system with point-of-care application, Mei Yan, Xiwei Huang, Revanth Nadipalli, Yang Shang, Hao Yu, Nanyang TechnologicalUniv.(Singapore);MinkyuJe,A*STARInstituteofMicroelectronics(Singapore);ChenXu,OmniVisionTechnologies,Inc.(UnitedStates);KiatsengYeo,NanyangTechnologicalUniv. (Singapore) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-03]


Smart SensorsSession Chair: Alice L. Reinheimer, e2v (United States)

Smart image sensor with adaptive correction of brightness, Michel Paindavoine, Auguste Ngoua, Olivier Brousse, Cedric Clerc, Univ. de Bourgogne (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-04]

Algorithm architecture co-design for ultra low-power image sensor, TimothéLaforest,CEA-LETI(France);AntoineDupret,Lab.d’ElectroniquedeTechnologiedel’Information(France);ArnaudVerdant,DidierLattard,PatrickVillard,CEA-LETI(France) . . . . . . . . . . . . . . . . . . . . . . . . .[8298-05]

A CMOS imager using focal-plane pinhole effect for confocal multi-beam scanning microscopy,Min-WoongSeo,AnWang,ZhuoLi,KeitaYasutomi, Keiichiro Kagawa, Shoji Kawahito, Shizuoka Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-06]

Time-to-impact sensors in robot vision applications based on the near-sensor image processing concept, Anders Astrom, Combitech AB (Sweden);RobertForchheimer,LinköpingUniv.(Sweden) . . . . . .[8298-07]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


SESSION 3 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm

High Performance SensorsSession Chair: Valérie Nguyen, Commissariatàl’ÉnergieAtomique

(France)

A 176x144 148dB adaptive tone-mapping imager, Sonia Vargas-Sierra, GustavoLiñán-Cembrano,ÁngelB.Rodríguez-Vázquez,Univ.deSevilla(Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-08]

A high-dynamic range (HDR) back-side illuminated (BSI) CMOS image sensor for extreme UV detection, Xinyang Wang, CMOSIS nv (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-09]

A low-noise, 15μm pixel-pitch, 640×512 hybrid InGaAs image sensor for night vision,FabriceGuellec,SébastienDubois,EricdeBorniol,PierreCastelein, Sébastien Martin, Romain Guiguet, Michaël Tchagaspanian, AnneRouvie,PhilippeBois,CEA-LETI(France) . . . . . . . . . . . . . .[8298-10]

High-dynamic range, 4 megapixel CMOS image sensor for scientific applications,PaulVu,BoydFowler,ChiaoLiu,SteveMims,PeterBartkovjak,HungDo,WangLi,JeffAppelbaum,AngelLopez,BAESystems Imaging Solutions (United States) . . . . . . . . . . . . . . . . .[8298-11]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pm

Noise and CharacterizationSession Chair: Kevin J. Matherson, Hewlett-Packard Co. (United

States)

Projecting the rate of in-field pixel defects based on pixel size, sensor area, and ISO,GlennH.Chapman,JennyLeung,AnaNamburete,SimonFraserUniv.(Canada);IsraelKoren,ZahavaKoren,Univ.ofMassachusettsAmherst (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-12]

Dynamic CCD pixel depletion edge model and the effects on dark current production,JustinC.Dunlap,MorleyM.Blouke,ErikBodegom,Ralf Widenhorn, Portland State Univ. (United States) . . . . . . . . . .[8298-13]

Characterizing the response of charge-couple device digital color cameras, Viktor Slavkovikj, Jon Yngve Hardeberg, Gjøvik Univ. College (Norway);AlexanderEichhorn,SimulaResearchLab.(Norway) . .[8298-14]

Implementing and using the EMVA1288 standard, Arnaud Darmont, Jean-FrançoisLemaitre,JawadChahiba,AphesaSPRL(Belgium)[8298-15]


Technological ImprovementsSession Chair: Xinyang Wang, CMOSIS nv (Belgium)

Development of high-transmittance, back-illuminated, silicon-on-sapphire substrates thinned below 25 micrometers and bonded to fused silica for high-quantum efficiency and high-resolution avalanche photodiode imaging arrays,AlvinG.Stern,AGStern,LLC(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-16]

29 mp, 35 mm format interline CCD image sensor,EricJ.Meisenzahl,DouglasA.Carpenter,JamesE.Doran,RobertP.Fabinski,StephenL.Kosman,JohnP.McCarten,EastmanKodakCo.(UnitedStates)[8298-17]

Photodiode dopant structure with atomically flat Si surface for high-sensitivity and stability to UV light, Taiki Nakazawa, Rihito Kuroda, Yasumasa Koda, Shigetoshi Sugawa, Tohoku Univ. (Japan) . . . .[8298-18]

New readout technique and performing edge detection designed to control vision sensors dataflow, Hawraa Amhaz, Gilles Sicard, TIMA Lab.(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-19]

Characterization of orthogonal transfer array CCDs for the WIYN one-degree imager,MichaelP.Lesser,DavidOuellette,TheUniv.ofArizona(UnitedStates);ToddBoroson,NationalOpticalAstronomyObservatory(UnitedStates);DanielHarbeck,PierreMartin,WIYNObservatory(UnitedStates);GeorgeJacoby,CarnegieObservatories(UnitedStates);JohnCavin,Univ.ofWisconsin-Madison(UnitedStates);DavidSawyer,NationalOpticalAstronomyObservatory(UnitedStates);KaseyBoggs,RichardBredthauer, Semiconductor Technology Associates Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-20]


Color ImagingSession Chair: Erik Bodegom, Portland State Univ. (United States)

Multispectral imaging device for help in diagnosis, Céline Delporte, Sylvie Sautrot, Mohamed Ben Chouikha, Univ. Pierre et Marie Curie (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-21]

Development of a driving method suitable to ultra-high-speed shooting in 2M-fps, 300k-pixel single-chip color camera, Jun Yonai, ToshikiArai,JapanBroadcastingCorp.(Japan);TetsuyaHayashida,NHKEngineeringServices,Inc.(Japan);HiroshiOhtake,JapanBroadcastingCorp.(Japan);TakeharuGojiEtoh,KinkiUniv.(Japan) . . . . . . . .[8298-22]

Experimental 120 fps color-image-capturing equipment with four 33-megapixel CMOS image sensors, Kohei Omura, Takayuki Yamashita, Ryohei Funatsu, Takuji Soeno, Masayuki Sugawara, NHK Science & TechnicalResearchLabs.(Japan) . . . . . . . . . . . . . . . . . . . . . . . .[8298-23]

Accurate color with increased sensitivity using IR,AmyEnge,EastmanKodak Co. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8298-24]

Improved computational color constancy using chromagenic filters in color filter arrays, Raju Shrestha, Gjøvik Univ. College (Norway)[8298-25]

Conference8298


Conference8299Monday-Tuesday 23-24 January 2012 • Proceedings of SPIE Vol. 8299

Digital Photography VIIIConference Chairs: Sebastiano Battiato, Univ.degliStudidiCatania(Italy);Brian G. Rodricks, FairchildImaging(UnitedStates);Nitin Sampat, Rochester Institute of Technology (United States)Conference Co-Chairs: Francisco H. Imai, CanonU.S.A.,Inc.(UnitedStates);Feng Xiao, Fairchild Imaging (United States)

Program Committee: Ajit S. Bopardikar, SamsungElectronics,IndiaSoftwareOperationsLtd.(India);Frédéric Cao, DxOLabs(France);Peter B. Catrysse, StanfordUniv.(UnitedStates);Ted J. Cooper, LensVector,Inc.(UnitedStates);Jeffrey M. DiCarlo, Intuitive Surgical, Inc. (United States);Alexandru F. Drimbarean, Tessera(FotoNation)IrelandLtd.(Ireland);Joyce E. Farrell, StanfordUniv.(UnitedStates);Guotong Feng, RicohInnovations,Inc.(UnitedStates);Boyd A. Fowler, FairchildImaging(UnitedStates);Sergio R. Goma, QualcommInc.(UnitedStates);Mirko Guarnera, STMicroelectronics(Italy);Xiaoyun Jiang, QualcommInc.(UnitedStates);George John, Motorola,Inc.(UnitedStates);Michael A. Kriss, Consultant(UnitedStates);Jiangtao Kuang, OmniVisionTechnologies,Inc.(UnitedStates);Feng Li, AptinaImagingCorp.(UnitedStates);J. Dylan Li, LifesizeCommunications,Inc.(UnitedStates);Kevin J. Matherson, Hewlett-PackardCo.(UnitedStates);Jon S. McElvain, DolbyLabs.,Inc.(UnitedStates);Ricardo J. Motta, NVIDIACorp.(UnitedStates);Seishi Ohmori, NikonCorp.(Japan);Manu Parmar, QualcommInc.(UnitedStates);Gloria G. Putnam, EastmanKodakCo.(UnitedStates);John R. Reinert-Nash, Lifetouch,Inc.(UnitedStates);Filippo D. Stanco, Univ. degli Studi di Catania(Italy);Qun Sun, AptinaImagingCorp.(UnitedStates);Sabine Süsstrunk, EcolePolytechniqueFédéraledeLausanne(Switzerland);Touraj Tajbakhsh, DreamChipTechnologies(Germany);Radka Tezaur, NikonPrecisionInc.(UnitedStates);Michael Wang, Cisco Systems, Inc. (United States);Dietmar Wüller, ImageEngineeringDietmarWüller(Germany);Weihua Xiong, OmniVisionTechnologies,Inc.(UnitedStates);Alireza Yasan, FoveonInc.(UnitedStates);Lei Zhang, The Hong Kong Polytechnic Univ. (Hong Kong, China)

Monday 23 JanuarySESSION 1 . . . . . . . . . . . . . . . . . Mon. 8:30 am to 12:10 pm

Sensors and OpticsSession Chair: Feng Li, Aptina Imaging Corp. (United States)

An objective protocol for comparing the noise performance of silver halide film and digital sensor, Frédéric Cao, Régis Tessières, Guichard Frédéric,HervéHornung,DxOLabs(France) . . . . . . . . . . . . . . . .[8299-01]

Sensor defect probability estimation and yield, Honghong Peng, Brian Keelan, Aptina Imaging Corp. (United States) . . . . . . . . . . . . . . . .[8299-02]

Optimum spectral sensitivity functions for single-sensor color imaging,ZahraSadeghipoor,EcolePolytechniqueFédéraledeLausanne(Switzerland);YueLu,HarvardSchoolofEngineeringandAppliedSciences(UnitedStates);SabineSüsstrunk,EcolePolytechniqueFédéraledeLausanne(Switzerland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-03]

A metric for the evaluation of wide dynamic-range cameras, Ping Wah Wong,PiximInc.(UnitedStates);YuHuaLu,MinistryofPublicSecurity(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-04]

Active pixels of transverse field detector based on a charge preamplifier,GiacomoLangfelder,CesareBuffa,AntonioFrancescoLongoni,AlicePelamatti,FedericoZaraga,PolitecnicodiMilano (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-05]

Digital focusing and re-focusing with thin multi-aperture cameras, AlexanderOberdörster,AndreasBrückner,FrankC.Wippermann,AndreasBräuer,Fraunhofer-InstitutfürAngewandteOptikundFeinmechanik(Germany);HendrikP.A.Lensch,Univ.Ulm(Germany) . . . . . . . .[8299-06]

The multi-focus plenoptic camera, Todor G. Georgiev, Adobe Systems Inc.(UnitedStates);AndrewLumsdaine,IndianaUniv.(UnitedStates)andAdobe Systems Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . .[8299-07]

Spatial domain analysis of discrete plenoptic sampling, Andrew Lumsdaine,IndianaUniv.(UnitedStates);TodorG.Georgiev,AdobeSystems Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-08]

Design framework for a spectral mask for a plenoptic camera, Kathrin Berkner, Sapna A. Shroff, Ricoh Innovations, Inc. (United States)[8299-09]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm

SESSION 2 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 5:20 pm

Image EnhancementSession Chair: Ajit S. Bopardikar, SamsungElectronics,India

SoftwareOperationsLtd.(India)

Detectability of structured noise,FengLi,BrianW.Keelan,AlexanderDokoutchaev, Robin Jenkin, Aptina Imaging Corp. (United States)[8299-10]

Reduced-reference image quality assessment based on statistics of edge patterns,YutingChen,XuanqinMou,Xi’anJiaotongUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-11]

Joint chromatic aberration correction and demosaicking, Tripurari Singh, Mritunjay Singh, Image Algorithmics (United States) . . . . .[8299-12]

Optimal defocus estimates from individual images for autofocusing a digital camera, Johannes Burge, Wilson S. Geisler, The Univ. of Texas at Austin (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-13]

Quality versus color saturation and noise, Brian W. Keelan, Robin B. Jenkin,ElaineW.Jin,AptinaImagingCorp.(UnitedStates). . . . .[8299-14]

Bio-inspired framework for automatic image quality enhancement, Francesca Gasparini, Schettini Raimondo, Ceresi Andrea, Marini Fabrizio, Univ. degli Studi di Milano-Bicocca (Italy) . . . . . . . . . . . . . . . . . . .[8299-15]

An efficient, multiple-exposure image fusion in JPEG domain, Ramya S.M.Hebbalaguppe,DublinCityUniv.(Ireland);RamakrishnaKakarala,Nanyang Technological Univ. (Singapore) . . . . . . . . . . . . . . . . . .[8299-16]

A controllable anti-aliasing filter for digital film cameras, Branko Petljanski, Panavision Inc. (United States) . . . . . . . . . . . . . . . . . .[8299-17]




Image Quality and Mobile Imaging I: Joint Session with Conference 8293


Development of the CPIQ spatial metrics,HenrikEliasson,SonyEricssonMobileCommunicationsAB(Sweden);DonaldBaxter,STMicroelectronics(R&D)Ltd.(UnitedKingdom);FrédéricCao,DxOLabs(France);JonathanPhillips,EastmanKodakCo.(UnitedStates) .[8293-01]

A functional-design approach to lens shading correction issues on mobile camera system,SeunghunYoo,SAMSUNGElectronicsCo.,Ltd.(Korea,Republicof);TaeChanKim,SAMSUNGElectronicsCo.,Ltd.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-18]

Rethinking user interfaces for cameraphones, Stephen A. Brewster, Christopher McAdam, Univ. of Glasgow (United Kingdom) . . . . .[8299-19]


Image Quality and Mobile Imaging II: Joint Session with Conference 8293


Calibration and adaptation of ISO visual noise for camera phone image quality assessment, Donald J. Baxter, Andrew Murray, STMicroelectronics(R&D)Ltd.(UnitedKingdom) . . . . . . . . . . . . .[8293-02]

An objective method for evaluating the texture-preserving capability of digital camcorders,KongfengZhu,ShujunLi,DietmarSaupe,Univ.Konstanz (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8293-03]

Improving texture loss measurement: spatial frequency response based on a colored target, Uwe Artmann, Dietmar Wueller, Image EngineeringGmbH&Co.KG(Germany) . . . . . . . . . . . . . . . . . . .[8293-04]

On the performances of computer vision algorithms on mobile platforms,SebastianoBattiato,GiovanniM.Farinella,EnricoMessina,GiovanniPuglisi,DanieleRavì,Univ.degliStudidiCatania(Italy);Alessandro Capra, Valeria Tomaselli, STMicroelectronics (Italy) .[8299-20]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


MultispectralSession Chair: Nitin Sampat, Rochester Institute of Technology

(United States)

Novel adaptive compression algorithm for hyperspectral images by using EDT and particle swarm optimization, Pedram Ghamisi, Farashid Sepehrband, Ali Mohammadzadeh, Mahmoud Reza Sahebi, K.N.Toosi Univ. of Technology (Iran, Islamic Republic of) . . . . . . . . . . . . . . .[8299-21]

Spectral sensitivity evaluation considering color constancy, Hideyasu Kuniba, Nikon Corp. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-22]

Multispectral demosaicking using guided filter, Yusuke Monno, Masayuki Tanaka, Masatoshi Okutomi, Tokyo Institute of Technology (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-23]

An LED-based lighting system for acquiring multispectral scenes, JoyceE.Farrell,ManuParmar,SteveLansel,StanfordUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-24]





Fast in-plane translation and rotation estimation for multi-image registration, Xiaoyun Jiang, Haiyin Wang, Qualcomm Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-25]

Multispectral filter wheel cameras: modeling aberrations for filters in front of lens, Julie Klein, Til Aach, RWTH Aachen (Germany) . . .[8299-26]

Correcting saturated pixels in images,JunFu,WenboJi,XuanqinMou,Xi’an Jiaotong Univ. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-27]

Real-time, multi-directional 2D fast wavelet transform and its denoised sharpening application, ByungJoon Baek, TaeChan Kim, SAMSUNGElectronicsCo.,Ltd.(Korea,Republicof) . . . . . . . . .[8299-28]

Color transfer using semantic image annotation, Francesca Gasparini, Raimondo Schettini, Claudio Cusano, Univ. degli Studi di Milano-Bicocca (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8299-29]

Adaptive directional color image sharpening with overshoot control, Touraj Tajbakhsh, Technische Univ. Hamburg-Harburg (Germany)[8299-30]


Conference8299


Conference 8300Tuesday-Wednesday 24-25 January 2012 • Proceedings of SPIE Vol. 8300

Image Processing: Machine Vision Applications VConference Chairs: Philip R. Bingham, OakRidgeNationalLab.(UnitedStates);Edmund Y. Lam, The Univ. of Hong Kong (Hong Kong, China)

Program Committee: Pierrick T. Bourgeat, Australiane-HealthResearchCtr.(Australia);Jun Cheng, ChineseAcademyofSciences(China);Michael J. Cree, TheUniv.ofWaikato(NewZealand);Laurent C. Duval, IFP(France);Ewald Fauster, MontanuniversitaetLoeben(Austria);Steven P. Floeder, 3MCo.(UnitedStates);David Fofi, Univ.deBourgogne(France);Luciano F. Fontoura Da Costa, Univ.deSãoPaulo(Brazil);Shaun Scott Gleason, OakRidgeNationalLab.(UnitedStates);Olivier Laligant, Univ.deBourgogne(France);Fabrice Meriaudeau, Univ. de Bourgogne (France);Dinesh Nair, NationalInstrumentsCorp.(UnitedStates);Kurt S. Niel, FachhochschuleWels(Austria);Arnau Oliver, Univ.deGirona(Spain);Vincent C. Paquit, OakRidgeNationalLab.(UnitedStates);Jeffery R. Price, Aldis,Inc.(UnitedStates);A. Ravishankar Rao, IBM Thomas J. WatsonResearchCtr.(UnitedStates);Hamed Sari-Sarraf, TexasTechUniv.(UnitedStates);Peter Schelkens, VrijeUniv.Brussel(Belgium);Ivan W. Selesnick, PolytechnicInstituteofNYU(UnitedStates);Ralph Seulin, Univ.deBourgogne(France);Christophe Stolz, Univ.deBourgogne(France);Yvon Voisin, Univ.deBourgogne(France);Gerald Zauner, Fachhochschule Wels (Austria)






Efficient local approximation of perceptual color differences for color inspection,ReinholdHuber-Mörk,AustrianInstituteofTechnology(Austria) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-16]

Modified fuzzy c-means applied to a Bragg-grating-based spectral imager for material clustering,AidaRodríguez,JuanLuisNieves,EvaValero,Univ.deGranada(Spain);EstíbalizGarrote,TECNALIA(Spain);Javier Hernández-Andrés, Javier Romero, Univ. de Granada (Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-17]

Robust recognition of 1D barcodes using hough transform, John Dwinell,LongXiangBian,SICK,Inc.(UnitedStates);PengBian,MicrosoftCorp. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-18]

Estimating the coordinates of pillars and posts in the parking lots for intelligent parking assist system, JaeHyung Choi, Jung Gap Kuk, Nam Ik Cho, Seoul National Univ. (Korea, Republic of) . . . . . . . . . . . . . . .[8300-19]

Image-processing-based quality control of osteo assay surface coating,MaximA.Sokolov,CorningScientificCtr.(RussianFederation);Terry Goodrich, Aravind Rammohan, Corning Incorporated (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-20]

Recognizing human gestures using a novel SVM tree, Hitesh Jain, Abhik Chatterjee, Sanjeev Kumar, Balasubramanian Raman, Indian Institute of Technology Roorkee (India) . . . . . . . . . . . . . . . . . . . . .[8300-21]

Fabric defect detection using the wavelet transform in an ARM processor, Jose Armando Fernandez Gallego, Antonio Nariño Univ. (Colombia);SergioAlejandroOrjuelaVargas,Univ.Gent(Belgium);JorgeAlvarez,AntonioNariñoUniv.(Colombia);WilfriedPhilips,Univ.Gent(Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-22]

Orthophotoplan segmentation based on regions merging for roof detection,YoussefElMerabet,CyrilMeurie,YassineRuichek,Univ.deTechnologiedeBelfort-Montbéliard(France);AbderrahmaneSbihi,EcoleNationaledesSciencesAppliquéesdeTanger(Morocco);RajjaTouahni,Univ. Ibn Tofail (Morocco) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-23]

Motion cue analysis for Parkinsonian gait recognition, Taha M. Khan, Jerker Westin, Mark Dougherty, Dalarna Univ. (Sweden) . . . . . . .[8300-24]


SESSION 1 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

SystemsSession Chair: Edmund Y. Lam, The Univ. of Hong Kong (Hong Kong,

China)

An introduction to omnidirectional vision: theory and applications, DavidFofi,SalehMosaddegh,AbdElRahmanShabayek,OlivierMorel,Univ. de Bourgogne (France). . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-01]

Sensor placement optimization in buildings, Simone Bianco, Raimondo Schettini, Francesco Tisato, Univ. degli Studi di Milano-Bicocca (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-02]

Optical feature extraction with illumination-encoded linear functions,RobinGruna,KarlsruherInstitutfürTechnologie(Germany);Jürgen Beyerer, Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-03]



AlgorithmsSession Chair: Philip R. Bingham, OakRidgeNationalLab.(United

States)

An illumination-invariant phase-shift algorithm in three-dimensional profilometry,FuqinDeng,TheUniv.ofHongKong(HongKong,China)andASMAssemblyAutomationLtd.(HongKong,China);EdmundY.Lam,TheUniv.ofHongKong(HongKong,China);WuifungSze,JiangwenDeng,KennethS.M.Fung,W.H.Leung,ASMAssemblyAutomationLtd.(Hong Kong, China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-04]

Fusing shape and texture features for pose-robust face recognition, Thorsten Gernoth, Rolf-Rainer Grigat, Technische Univ. Hamburg-Harburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-05]

Automated inspection of tubular material based on magnetic particle inspection, Adhiguna Mahendra, Christophe Stolz, Fabrice Meriaudeau, Univ.deBourgogne(France);SebastienPetit,AlexandreNoel,FabienDegoutin, Vallourec S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . .[8300-06]

Intermediate-level segmentation of color images through perception and geometry-based contour completions and shape cuts, Jacopo Grazzini,LakshmanPrasad,LosAlamosNationalLab. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-07]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm

Detection and TrackingSession Chair: David Fofi, Univ. de Bourgogne (France)

Runway hazard detection in poor visibility conditions, Bo Jiang, NationalInstituteofAerospace(UnitedStates);Zia-urRahman,OldDominion Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-08]

Application of image processing to track twin boundary motion in magnetic shape memory alloys,AdrianRothenbuhler,ElisaH.BarneySmith, Peter Müllner, Boise State Univ. (United States) . . . . . . . .[8300-09]

A new point process model for trajectory-based events annotation, NicolasBallas,CEALIST(France)andMinesParisTech(France);BertrandDelezoide,CEALIST(France);FrançoisePrêteux,MinesParisTech(France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-10]

Face detection and eyeglasses detection for thermal face recognition, YufengZheng,AlcornStateUniv.(UnitedStates) . . . . . . . . . . . .[8300-11]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pm

ApplicationsSession Chair: Philip R. Bingham, OakRidgeNationalLab.(United

States)

Combining spatial and spectral information to improve crop/weed discrimination algorithms, Gawain Jones, Sylvain Villette, Jean-Noel Paoli, Christelle Gée, AgroSup Dijon (France) . . . . . . . . . . . . . . . .[8300-12]

Automated parasite detection in clams by transillumination imaging and pattern classification,MiguelE.Soto,PabloA.Coelho,SergioN.Torres, Daniel G. Sbarbaro, Univ. de Concepción (Chile) . . . . . . .[8300-13]

Vision-based, in-line fabric defect detection using yarn-specific shape features, Dorian Schneider, Til Aach, RWTH Aachen (Germany) .[8300-14]

3D temperature mapping of turboshaft components using thermal paints and color recognition, Samuel Guérin, Turbomeca SA (France) andONERA,TheFrenchAerospaceLab(France);ChristineLempereur,ONERA,TheFrenchAerospaceLab.(France);PhilippeBrevet,TurbomecaSA (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8300-15]

Conference 8300


Conference 8301Monday-Tuesday 23-24 January 2012 • Proceedings of SPIE Vol. 8301

Intelligent Robots and Computer Vision XXIX: Algorithms and TechniquesConference Chairs: Juha Röning, Univ.ofOulu(Finland);David P. Casasent, Carnegie Mellon Univ. (United States)

Program Committee: Norbert Lauinger, CORRSYS3DSensorsAG(Germany);Dah Jye Lee, BrighamYoungUniv.(UnitedStates);Charles A. McPherson, DraperLab.(UnitedStates);Kurt S. Niel, FachhochschuleWels(Austria);Yoshihiko Nomura, MieUniv.(Japan);Daniel Raviv, Florida AtlanticUniv.(UnitedStates);Oliver Sidla, SLREngineeringOG(Austria);Bernard L. Theisen, U.S. Army Tank Automotive Research, Development andEngineeringCtr.(UnitedStates);Dili Zhang, Monotype Imaging (United States)

Monday 23 JanuarySESSION 1 . . . . . . . . . . . . . . . . . . . . . .Mon. 8:20 to 9:50 am

Invited Papers on Intelligent RoboticsSession Chair: Juha Röning, Univ. of Oulu (Finland)

Software-based, neural-network-assisted movement compensation for nanoresolution piezo actuators (Invited Paper),JuhaRöning,MarkoKauppinen, Univ. of Oulu (Finland) . . . . . . . . . . . . . . . . . . . . . . . .[8301-01]

Traffic monitoring with distributed smart cameras (Invited Paper), Oliver Sidla,MarcinRosner,SLREngineeringOG(Austria);MichaelUlm,AustrianInstitute of Technology (Austria) . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-02]

The 19th annual intelligent ground vehicle competition: student-built autonomous ground vehicles (Invited Paper),BernardL.Theisen,U.S.ArmyTankAutomotiveResearch,DevelopmentandEngineeringCtr.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-03]

SESSION 2 . . . . . . . . . . . . . . . . . Mon. 9:50 am to 12:10 pm

Stereo Vision and ApplicationsSession Chair: Juha Röning, Univ. of Oulu (Finland)

Accurate, dense 3D reconstruction of moving and still objects from dynamic stereo sequences based on temporal modified-RANSAC and feature-cut, Naotomo Tatematsu, Jun Ohya, Waseda Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-04]

Efficient hybrid monocular-stereo approach to on-board, video-based traffic sign detection and tracking,JavierMarinas,LuisSalgado,Univ.Politécnica de Madrid (Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-05]

A general model and calibration method for spherical stereoscopic vision,WeijiaFeng,TianjinUniv.(China);JuhaRöning,JuhoKannala,Univ.ofOulu(Finland);BaofengZhang,TianjinUniv.(China) . . . .[8301-06]

An approach to stereo-point cloud registration using image homographies,StephenD.Fox,DamianM.Lyons,FordhamUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-07]

Hazardous sign detection for safety applications in traffic monitoring, WandaBenesova,SlovakUniv.ofTechnology(Slovakia);OliverSidla,SLREngineeringOG(Austria);MichalKottman,SlovakUniv.ofTechnology(Slovakia);ElenaSikudova,ZuzanaCernekova,ComeniusUniv.inBratislava (Slovakia) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-08]

PRoViScout: a planetary scouting rover demonstrator, Gerhard M. Paar,JOANNEUMRESEARCHForschungsgesellschaftmbH(Austria);MarkWoods,SciSysLtd.(UnitedKingdom);ChristianeGimkiewicz,Ctr.Suissed’ElectroniqueetdeMicrotechniqueSA(Switzerland);FredLabrosse,AberystwythUniv.(UnitedKingdom);AlbertoMedina,GMVS.A.(Spain) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-09]

LunchBreak . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:10to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Mon. 2:00 to 3:40 pm

Novel People and Vehicle Tracking ApproachesSession Chair: Oliver Sidla, SLREngineeringOG(Austria)

Red-light traffic enforcement at railway crossings, Oliver Sidla, Marcin Rosner,SLREngineeringOG(Austria) . . . . . . . . . . . . . . . . . . . . .[8301-10]

Image projection clues for improved real-time vehicle tracking in tunnels, Vedran Jelaca, Jorge Oswaldo Niño-Castaneda, Aleksandra Pizurica, Wilfried Philips, Univ. Gent (Belgium) . . . . . . . . . . . . . . .[8301-11]

Decentralized tracking of humans using a camera network, Sebastian Gruenwedel, Vedran Jelaca, Jorge Oswaldo Niño-Castañeda, Peter Van Hese, Dimitri Van Cauwelaert, Peter Veelaert, Wilfried Philips, Univ. Gent (Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-12]

Real-time detection of traffic events using smart cameras, Marko M. Macesic,Tehnomobil-Protech(Serbia);VedranJelaca,JorgeOswaldoNiño-Castaneda,Univ.Gent(Belgium);NenadProdanovic,MarkoPanic,Univ.ofNoviSad(Serbia);AleksandraPizurica,Univ.Gent(Belgium);VladimirCrnojevic,Univ.ofNoviSad(Serbia);WilfriedPhilips,Univ.Gent(Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-13]

Mixed road traffic: data acquisition, optical tracking, and microscopic modeling,RobertSchönauer,TechnischeUniv.Graz(Austria);YuriyLypetskyy,SLREngineeringOG(Austria) . . . . . . . . . . . . . . . . . . .[8301-14]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Mon. 4:00 to 5:20 pm

UAVs and Aerial ApplicationsSession Chair: Terrell N. Mundhenk, HRLLabs.,LLC(UnitedStates)

AR.Drone: security threat analysis and exemplary attack to track objects or persons, Jana Fruth, Mario Hildebrandt, Tobias Hoppe, Jana Dittmann, Otto-von-Guericke-Univ. Magdeburg (Germany) . . . . .[8301-15]

Detection of unknown targets from aerial camera and extraction of simple object fingerprints for the purpose of target reacquisition, Terrell N. Mundhenk, Kang-Yu Ni, Yang Chen, Kyungnam Kim, Yuri Owechko,HRLLabs.,LLC(UnitedStates) . . . . . . . . . . . . . . . . . .[8301-16]

Vision-based geolocation from micro-aerial-vehicle-captured (MAV) images, Jaco Cronje, Council for Scientific and Industrial Research (South Africa)andUniv.ofJohannesburg(SouthAfrica);AndreNel,Univ.ofJohannesburg (South Africa) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-17]

Superresolution terrain map enhancement for navigation based on satellite imagery, Jeremy Straub, Jacksonville State Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-18]




Robot Manipulation and ApplicationSession Chair: Yoshihiko Nomura, Mie Univ. (Japan)

3D positional control of magnetic levitation system using adaptive control: improvement of positioning control in horizontal plane, ToshimasaNishino,NorihikoKato,MieUniv.(Japan);NaoakiTsuda,WakayamaNationalCollegeofTechnology(Japan);YoshihikoNomura,Mie Univ. (Japan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-19]

Robots in agriculture: an I-weed robot for a specific spraying, Ghislain Salis, Christelle Gée, Sylvain Villette, Jean-Noel Paoli, Gawain Jones, AgroSup Dijon (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-20]

The magic glove: a gesture-based remote controller for intelligent mobile robots,ChaominLuo,YueChen,MohanKrishnan,MarkPaulik,Univ. of Detroit Mercy (United States) . . . . . . . . . . . . . . . . . . . . . .[8301-21]

Way-point navigation for a skid steer vehicle in unknown environments, Peiyi Chen, Arun Das, Prasenjit Mukherjee, Steven Waslander, Univ. of Waterloo (Canada) . . . . . . . . . . . . . . . . . . . .[8301-22]


Vision Navigation and Activity RecognitionSession Chair: Charles A. McPherson, DraperLab.(UnitedStates)

Integrated field testing of planetary robotics vision processing: the PRoVisG campaign in Tenerife 2011,GerhardM.Paar,JOANNEUMRESEARCHForschungsgesellschaftmbH(Austria);LesterWaugh,EADSAstriumLtd.(UnitedKingdom);DavidP.Barnes,AberystwythUniv.(UnitedKingdom);TomasPajdla,CzechTechnicalUniv.inPrague(CzechRepublic);MarkWoods,SciSysLtd.(UnitedKingdom);Hans-RudolfGraf,Ctr.Suissed’ElectroniqueetdeMicrotechniqueSA(Switzerland);YangGao,Univ.ofSurrey(UnitedKingdom);KonradWillner,TechnischeUniv.Berlin(Germany);Jan-PeterA.Muller,Univ.CollegeLondon(UnitedKingdom);RongxingLi,TheOhioStateUniv.(UnitedStates);MichelMaurette, Ctr. National d’Études Spatiales (France) . . . . . . . . . . .[8301-23]

Hierarchical loop detection for mobile outdoor robots, Christian Winkens,DagmarLang,MarcelHäselich,DietrichW.Paulus,Univ.Koblenz-Landau(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-24]

A novel margin-based, linear embedding technique for visual object recognition,FadiDornaika,Univ.delPaísVasco(Spain) . . . . . .[8301-25]

Real-time, two-level foreground detection and person-silhouette extraction enhanced by body-parts tracking, Rada Deeb, Élodie Desserée,SaidaBouakaz,Univ.ClaudeBernardLyon1(France) [8301-26]

Activity recognition from video using layered approach, Charles A. McPherson,JohnM.Irvine,MonYoung,DraperLab.(UnitedStates);Anthony Stefanidis, George Mason Univ. (United States). . . . . . .[8301-27]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:50to2:00pm


Visual AlgorithmsSession Chairs: David P. Casasent, Carnegie Mellon Univ. (United

States);Oliver Sidla, SLREngineeringOG(Austria)

Method for fast detecting the intersection of a plane and a cube in an octree structure to find point sets within a convex region, Keisuke Fujimoto,NobutakaKimura,ToshioMoriya,Hitachi,Ltd.(Japan) [8301-28]

A study of the sensitivity of long-range, passive-ranging techniques to atmospheric scintillation, Jason P. de Villiers, Council for Scientific and IndustrialResearch(SouthAfrica)andUniv.ofCapeTown(SouthAfrica);Fred C. Nicolls, Univ. of Cape Town (South Africa) . . . . . . . . . . .[8301-29]

Lucas-Kanade image registration using camera motions, Sunghyun Cho, Hojin Cho, Pohang Univ. of Science and Technology (Korea, Republic of);YoungSuMoon,JungukCho,ShihwaLee,SamsungElectronicsCo.,Ltd.(Korea,Republicof);SeungyongLee,PohangUniv.ofScienceandTechnology (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-30]

Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter, Stefano Rosa, Marco Paleari, Paolo Ariano, IstitutoItalianodiTecnologia(Italy);BasilioBona,PolitecnicodiTorino(Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-31]

A modular real-time vision system for humanoid robots,AlinaL.Trifan,AntónioJ.R.Neves,BernardoCunha,NunoLau,Univ.deAveiro (Portugal) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-32]


Intelligent Ground Vehicle CompetitionSession Chair: Bernard L. Theisen, U.S. Army Tank Automotive Research,DevelopmentandEngineeringCtr.(UnitedStates)

Radial polar histogram approach to obstacle avoidance and path planning for robotic cognition and motion control, Po-Jen Wang, NicholasR.Keyawa,CraigEuler,C.T.Lin,CaliforniaStateUniv.,Northridge (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-33]

Optimising a mobile robot control system with GPU acceleration, Nat Tuck,MichaelE.McGuinness,FredMartin,Univ.ofMassachusettsLowell(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-34]

Design and realization of an intelligent ground vehicle with modular payloads, Mehmet A. Akmanalp, Ryan M. Doherty, Jeffrey Gorges, Peter Kalauskas,EllenPeterson,FelipePolido,StephenS.Nestinger,TaskinPadir, Worcester Polytechnic Institute (United States) . . . . . . . . .[8301-35]

Navigating a path delineated by colored flags: an approach for an IGVC 2011 requirement, Alex Szmatula, Matt Parrish, Mohan Krishnan, MarkPaulik,UtaybaMohammad,ChaominLuo,Univ.ofDetroitMercy(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-36]

Navigating with VFH: a strategy to avoid traps,ChaominLuo,MohanKrishnan, Mark Paulik, Utayba Mohammad, Univ. of Detroit Mercy (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-37]





Measurement of noises and modulation transfer function of cameras used in optical-digital correlators,NikolayN.Evtikhiev,SergeyN.Starikov, Pavel A. Cheryomkhin, Vitaly V. Krasnov, National Research NuclearUniv.MEPhI(RussianFederation) . . . . . . . . . . . . . . . . . .[8301-38]

A phase-space approach for detection and removal of rain in video, Varun Santhaseelan, K. Vijayan Asari, Univ. of Dayton (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8301-39]

Intelligence algorithms for autonomous navigation in a ground vehicle, Steve J. Petkovsek, Adam Norton, Trinity College (United States)[8301-40]

Hierarchical, multi-level image mosaicing for autonomous navigation of UAV, Sangho Park, Debabrata Ghosh, Naima Kaabouch, Ronald Fevig, William Semke, The Univ. of North Dakota (United States) . . . . .[8301-41]


Conference 8301


Conference 8302Wednesday-Thursday 25-26 January 2012 • Proceedings of SPIE Vol. 8302

Imaging and Printing in a Web 2.0 World IIIConference Chairs: Qian Lin, Hewlett-PackardLabs.(UnitedStates);Jan P. Allebach, PurdueUniv.(UnitedStates);Zhigang Fan, Xerox Corp. (United States)

Program Committee: Patricia Albanese, RochesterInstituteofTechnology(UnitedStates);Kathrin Berkner, RicohInnovations,Inc.(UnitedStates);Susanne Christine Johanna Boll, Univ.ofOldenburg(Germany);Reiner Fageth, CeWeColorAG&Co.OHG(Germany);Xiaofan Lin, Vobile, Inc. (UnitedStates);Jerry Liu, Hewlett-PackardLabs.(UnitedStates);Jiebo Luo, EastmanKodakCo.(UnitedStates);Robert J. Rolleston, Xerox Corp. (UnitedStates);David N. Slatter, Hewlett-PackardLabs.(UnitedKingdom);Yonghong Tian, PekingUniv.(China);Shengjin Wang, Tsinghua Univ. (China);Wiley H. Wang, Shutterfly (United States)



SESSION 1 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Industrial Applications IOrganizing visual moments for sharing and reflections: VisR (Invited Paper), Ramesh C. Jain, Univ. of California, Irvine (United States) [8302-01]

The role of digital presses, Web 2.0, and mobile in enabling the internet of things (Invited Paper), Tony F. Rodriguez, Digimarc Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-02]


Industrial Applications IIMobile image processing for fashion marketplace (Invited Paper), Manish Chandra, Gautam Golwala, Chetan Pungaliya, Poshmark, Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-03]

Mobile capture: the end of the photocopier? (Invited Paper), Michael J. Gormish, Ricoh Innovations, Inc. (United States) . . . . . . . . . . . . .[8302-04]

From scenes to screens: connected digital imaging (Invited Paper),ZivGillat,Eye-Fi(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-05]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm

Web Printing and AnalysisText documents as social networks, Helen Balinsky, Hewlett-Packard Labs.(UnitedKingdom);AlexanderBalinsky,CardiffUniv.(UnitedKingdom);StevenJ.Simske,Hewlett-PackardCo.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-06]

Retrieval of a webpage from its hardcopy,ZhigangFan,XeroxCorp.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-07]

HP2.ME (URL) shorten service,HuaZhang,WeiXiaoWu,YuZhang,CanZheng,Hewlett-PackardChinaCo.,Ltd.(China);QianLin,JerryLiu,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . . . . . .[8302-08]

HP Smartprint,HuaZhang,ZhenLiu,YueYuan,GuoJiaLiao,Hewlett-PackardChinaCo.,Ltd.(China);QianLin,JerryLiu,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-09]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pm

Online Photo ServicesKind of images in printed photo books, Reiner Fageth, Peter Schuetz, Thomas Wagner, CeWe Color AG & Co. OHG (Germany) . . . . . .[8302-10]

SmartFit: automatic photo fitting for variable data printing,ZachiKarni,AmirGaash,Hewlett-PackardLabs.IsraelLtd.(Israel) . . . . . . . . .[8302-11]

All new custom path photo book creation, Wiley H. Wang, Russ Muzzolini, Shutterfly (United States) . . . . . . . . . . . . . . . . . . . . . . .[8302-12]

Investigation of the role of aesthetics in differentiating between photographs taken by amateur and professional photographers, Shao-FuXue,PurdueUniv.(UnitedStates);QianLin,DanielTretter,SeungyonLee,Hewlett-PackardLabs.(UnitedStates);ZygmuntPizlo,JanP. Allebach, Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . .[8302-13]


Social Media and Mobile Document ApplicationsLearning from user data in Facebook (Invited Paper), Jun Yang, Facebook Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-14]

Measuring engagement effectiveness in social media: a time-sensitive methodology,TongSun,LeiLi,WeiPeng,XeroxCorp.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-15]

Building a scalable storage for images on a social network, Jaime Medrano Navarro, Tuenti Technologies (Spain) . . . . . . . . . . . . . .[8302-16]

Color correction of smartphone photos with prior knowledge, Yonghui Zhao,Shen-geWang,XeroxCorp.(UnitedStates);JunJiang,RochesterInstitute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8302-17]

XML data compression in web publishing, Ruiheng Qiu, Peking Univ. (China)andStateKeyLab.ofDigitalPublishingTechnology(China);WeiHu,ZhiTang,XiaoqingLu,PekingUniv.(China). . . . . . . . . . . . . .[8302-18]



Layout Analysis and CreationLayout hierarchies for interactive design reuse, Darryl S. Greig, Andrew A.Hunter,DavidN.Slatter,Hewlett-PackardLabs.(United Kingdom) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-19]

Automatic page composition with combined cropping and layout technologies, Andrew A. Hunter, David N. Slatter, Darryl S. Greig, Hewlett-PackardLabs.(UnitedKingdom) . . . . . . . . . . . . . . . . . . .[8302-20]

Psychophysical evaluation of document visual similarity, Aziza Satkhozhina,IldusAhmadullin,PurdueUniv.(UnitedStates);SeungyonLee,Hewlett-PackardCo.(UnitedStates);ZygmuntPizlo,JanP.Allebach,Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-21]

Similarity pyramid: browsing a document database with respect to visual similarity, Ildus Ahmadullin, Jan P. Allebach, Purdue Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-22]

Automatic design of magazine covers, Ali Jahanian, Purdue Univ. (UnitedStates)andHewlett-PackardLabs.(UnitedStates);JanP.Allebach,PurdueUniv.(UnitedStates);QianLin,JerryLiu,NiranjanDamera-Venkata,EamonnO’Brien-Strain,SeungyonLee,JianFan,DanielTretter,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . .[8302-23]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to2:00pm


Content UnderstandingSentiment analysis and live customer intelligence from social channels (Invited Paper),MeichunHsu,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-24]

Automatic content recognition for the next-generation TV experience, XiaofanLin,Vobile,Inc.(UnitedStates) . . . . . . . . . . . . . . . . . . . .[8302-25]

Marketing image categorization using hybrid human-machine combinations, Nathan Gnanasambandam, Xerox Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-26]

Practical experiences in analog to digital content transformation, PrakashD.Reddy,Hewlett-PackardLabs.(UnitedStates) . . . . .[8302-27]

Global image analysis to determine suitability for text-based image personalization,HengzhouDing,RajaBala,ZhigangFan,XeroxCorp.(UnitedStates);CharlesA.Bouman,JanP.Allebach,PurdueUniv.(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8302-28]

Chrominance watermark embed using a full-color visibility model, Alastair M. Reed, Digimarc Corp. (United States) . . . . . . . . . . . . .[8302-29]

Document image orientation based on both text and image, ChangsongLiu,TsinghuaUniv.(China) . . . . . . . . . . . . . . . . . . . .[8302-30]

Conference 8302


Conference 8303Monday-Wednesday 23-25 January 2012 • Proceedings of SPIE Vol. 8303

Media Watermarking, Security, and Forensics 2012Conference Chairs: Nasir D. Memon, PolytechnicInstituteofNYU(UnitedStates);Adnan M. Alattar, DigimarcCorp.(UnitedStates);Edward J. Delp III, Purdue Univ. (United States)

Program Committee: Mauro Barni, Univ.degliStudidiSiena(Italy);Jeffrey A. Bloom, DialogicMediaLabs(UnitedStates);Scott A. Craver, BinghamtonUniv.(UnitedStates);Jana Dittmann, Otto-von-Guericke-Univ.Magdeburg(Germany);Gwenaël Doërr, TechnicolorS.A.(France);Jessica Fridrich, BinghamtonUniv.(UnitedStates);Jiwu Huang, SunYat-SenUniv.(China);Ton Kalker, Hewlett-PackardCo.(UnitedStates);Andrew D. Ker, Univ.ofOxford(UnitedKingdom);Alex Chichung Kot, NanyangTechnologicalUniv.(Singapore);Bangalore Manjunath, Univ. of California,SantaBarbara(UnitedStates);Regunathan Radhakrishnan, DolbyLabs.,Inc.(UnitedStates);Husrev Taha Sencar, TOBBEkonomiveTeknolojiÜniv.(UnitedStates);Gaurav Sharma, Univ.ofRochester(UnitedStates);Claus Vielhauer, Otto-von-Guericke-Univ.Magdeburg(Germany);Svyatoslav V. Voloshynovskiy, Univ.ofGeneva(Switzerland);Min Wu, Univ.ofMaryland,CollegePark(UnitedStates);Chang D. Yoo, KAIST (Korea, Republic of)

Monday 23 JanuaryKeynote Presentation I . . . . . . . . . Mon. 8:20 to 9:20 am

Session Chair: Adnan M. Alattar, Digimarc Corp. (United States)

Watermarking and fingerprinting for audience measurement (Presentation Only), Arun Ramaswamy, Nielsen Media Research (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8303-28]

SESSION 1 . . . . . . . . . . . . . . . . . . . . .Mon. 9:20 to 10:10 am

SecuritySession Chair: Scott A. Craver, Binghamton Univ. (United States)

Security threat to media security applications based on scale-space feature extraction,Chao-YongHsu,AcademiaSinica(Taiwan);Chun-ShienLu,InstituteofInformationScience(Taiwan);Soo-ChangPei,National Taiwan Univ. (Taiwan) . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-01]

Robust image obfuscation for privacy protection in Web 2.0 applications,AndreasPoller,MartinSteinebach,HuajianLiu,Fraunhofer-Institut für Sichere Informations-Technologie (Germany) . . . . . . .[8303-02]


WatermarkSession Chair: Gaurav Sharma, Univ. of Rochester (United States)

Improved Fourier domain template and patchwork embedding using spatial masking,HuajianLiu,MartinSteinebach,Fraunhofer-InstitutfürSichere Informations-Technologie (Germany) . . . . . . . . . . . . . . . .[8303-03]

Ranking search for probabilistic fingerprinting codes,MarcelSchäfer,Waldemar Berchtold, Martin Steinebach, Fraunhofer-Institut für Sichere Informations-Technologie (Germany) . . . . . . . . . . . . . . . . . . . . . .[8303-04]

Stereoscopic watermarking by horizontal noise mean shifting, Ji-Won Lee,Hee-DongKim,Heung-KyuLee,KAIST(Korea,Republicof) [8303-05]

Reversible q-ry watermarking with controllable prediction error and location map-free capability,TatianaEfimushkina,KarenO.Egiazarian,Tampere Univ. of Technology (Finland) . . . . . . . . . . . . . . . . . . . . .[8303-06]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:20to2:00pm

Video 1: Dialogic . . . . . . . . . . . . . . . . Mon. 2:00 to 2:15 pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Mon. 2:15 to 3:30 pm

Steganalysis ISession Chair: Jessica Fridrich, Binghamton Univ. (United States)

Optimizing pixel predictors for steganalysis, Vojtech Holub, Jessica Fridrich, Binghamton Univ. (United States) . . . . . . . . . . . . . . . . . .[8303-07]

Steganalysis of JPEG images using rich models, Jan Kodovsky, Jessica Fridrich, Binghamton Univ. (United States) . . . . . . . . . . . . . . . . . .[8303-08]

Co-occurrence steganalysis in high dimension, Tomas Pevny, Czech Technical Univ. in Prague (Czech Republic) . . . . . . . . . . . . . . . . .[8303-09]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Mon. 4:00 to 5:00 pm

Guest Speaker 1Session Chair: Adnan M. Alattar, Digimarc Corp. (United States)

Advancing technology: bane and boon for banknotes (Presentation Only),SaraE.Church,BoardofGovernorsoftheFederalReserveSystem(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-10]


Keynote Presentation II . . . . . . . Tues. 9:30 to 10:30 amSession Chair: Adnan M. Alattar, Digimarc Corp. (United States)

The landscape of mobile payments (Presentation Only), Darko Kirovski, Microsoft Research Cambridge (United Kingdom) . . [8303-29]


ForensicsSession Chair: Gwenaël Doërr, Technicolor S.A. (France)

Downscale-tolerant camcorder identification, Dai-Kyung Hyun, Min-JeongLee,Heung-KyuLee,KAIST(Korea,Republicof) . . . . . . .[8303-11]

Digital image forensics for photographic copying, Yanmei Fang, Jing Yin, Sun Yat-Sen Univ. (China) . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-12]

Forensic audio watermark detection, Martin Steinebach, Sascha Zmudzinski,Fraunhofer-InstitutfürSichereInformations-Technologie(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-13]

Identifying images corrected for lens distortion using sensor fingerprints, Miroslav Goljan, Jessica Fridrich, Binghamton Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-14]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


Video 2: Civolution . . . . . . . . . . . . . . . Tues. 2:00 to 2:08 pm

Video 3: Night Vision Lab . . . . . . . . . Tues. 2:08 to 2:15 pm


AuthenticationSession Chair: Ton Kalker, Hewlett-Packard Co. (United States)

Digital audio authentication by robust feature embedding, Sascha Zmudzinski,BadarMunir,MartinSteinebach,Fraunhofer-InstitutfürSichere Informations-Technologie (Germany) . . . . . . . . . . . . . . . .[8303-15]

High-resolution printed amino acid traces: a first-feature extraction approach for fingerprint forgery detection, Mario Hildebrandt, Stefan Kiltz, Jana Dittmann, Otto-von-Guericke-Univ. Magdeburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-16]

Image forgery detection by means of no-reference quality metrics, Federica Battisti, Marco Carli, Alessandro Neri, Univ. degli Studi di Roma Tre (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-17]


Guest Speaker 2Session Chair: Nasir D. Memon, Polytechnic Institute of NYU (United

States)

Privacy on the social network (Presentation Only), Jessica Staddon, Google Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-18]


SESSION 8 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:20 am

Steganalysis IISession Chair: Andrew D. Ker, Univ. of Oxford (United Kingdom)

Going from small to large data in steganalysis,IvansLubenko,AndrewD. Ker, Univ. of Oxford (United Kingdom) . . . . . . . . . . . . . . . . . . .[8303-19]

Identifying a steganographer in realistic and heterogeneous data sets, AndrewD.Ker,Univ.ofOxford(UnitedKingdom);TomasPevny,CzechTechnical Univ. in Prague (Czech Republic) . . . . . . . . . . . . . . . . .[8303-20]


FingerprintingSession Chair: Regunathan Radhakrishnan, DolbyLabs.,Inc.(United

States)

Asymmetric robust quantum image hashing, Martin Steinebach, Huajian Liu,Fraunhofer-InstitutfürSichereInformations-Technologie (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-21]

Fast detection of Tardos codes with Boneh-Shaw types, Mathieu Desoubeaux,GaëtanLeGuelvouit,FranceTelecomR&D(France);WilliamPuech,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-22]

Locatability of modified pixels in steganographic images, Tu-Thach Quach,SandiaNationalLabs.(UnitedStates) . . . . . . . . . . . . . . .[8303-23]

Forensic characterization of camcorded movies: digital cinema versus celluloid film prints, Xavier Rolland-Neviere, Bertrand Chupeau, Gwenaël Doërr,LaurentBlondé,TechnicolorS.A.(France) . . . . . . . . . . . . .[8303-24]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

Video 4: MarkAny . . . . . . . . . . . . . . . . Wed. 2:00 to 2:15 pm

SESSION 10 . . . . . . . . . . . . . . . . . . . . Wed. 2:15 to 3:30 pm

MiscellaneousSession Chair: Jeffrey A. Bloom, DialogicMediaLabs(UnitedStates)

Extending a context model for microphone forensics,ChristianKrätzer,Kun Qian, Jana Dittmann, Otto-von-Guericke-Univ. Magdeburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8303-25]

Simulating large-scale acoustic path benchmarking, Michael Arnold, Peter Baum, Manuel Alonso, Ulrich Gries, Deutsche Thomson oHG (Germany);GwenaëlDoërr,TechnicolorS.A.(France) . . . . . . . . .[8303-26]

Noise removing in encrypted color image by statistical analysis, NaveedIslam,WilliamPuech,Lab.d’InformatiquedeRobotiqueetdeMicroelectroniquedeMontpellier(France) . . . . . . . . . . . . . . . . . .[8303-27]

Conference 8303


Conference8304ATuesday-Wednesday 24-25 January 2012 • Proceedings of SPIE Vol. 8304A

Multimedia on Mobile Devices 2012Conference Chairs: Reiner Creutzburg, FachhochschuleBrandenburg(Germany);David Akopian, The Univ. of Texas at San Antonio (United States)

Program Committee: Sos S. Agaian, TheUniv.ofTexasatSanAntonio(UnitedStates);Nina T. Bhatti, Hewlett-PackardLabs.(UnitedStates);Faouzi Alaya Cheikh, GjøvikUniv.College(Norway);Linda Breitlauch, MediadesignHochschuleDüsseldorf(Germany);Chang Wen Chen, Univ. at Buffalo(UnitedStates);Philip C. L. Chen, TheUniv.ofTexasatSanAntonio(UnitedStates);Kenneth J. Crisler, Motorola,Inc.(UnitedStates);David Scott Doermann, Univ.ofMaryland,CollegePark(UnitedStates);Elizabeth Dykstra-Erickson, Kinoma(UnitedStates);Stefan Edlich, Technische FachhochschuleBerlin(Germany);Atanas P. Gotchev, TampereUniv.ofTechnology(Finland);Lajos Hanzo, Univ. of Southampton (United Kingdom);Zhihai He, Univ.ofMissouri-Columbia(UnitedStates);Hendrik O. Knoche, Univ.CollegeLondon(UnitedKingdom);Catalin Lacatus, TelcordiaTechnologies,Inc.(UnitedStates);Xin Li, WestVirginiaUniv.(UnitedStates);Manzur M. Murshed, MonashUniv.(Australia);Sethuraman Panchanathan, ArizonaStateUniv.(UnitedStates);Kari A. Pulli, NokiaResearchCtr.(UnitedStates);Matthias Rauterberg, Technische Univ. Eindhoven(Netherlands);Phillip A. Regalia, TELECOM&ManagementSudParis(France);René Rosenbaum, Univ. of California, Davis (United States);Phanikrishna K. Sagiraju, TheUniv.ofTexasatSanAntonio(UnitedStates);Abhay Samant, NationalInstruments(India);Thomas Schwotzer, FHTW(Germany);Olli Silvén, Univ.ofOulu(Finland);Jarmo Henrik Takala, TampereUniv.ofTechnology(Finland);Haitao Zheng, Univ. of California, Santa Barbara (United States)






Low-complexity bit-plane entropy coding for 3D DWT-based video compression,EvgenyA.Belyaev,KarenO.Egiazarian,TampereUniv.ofTechnology (Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-16]

Raster image adaptation for mobile devices using profiles, René Rosenbaum, Bernd Hamann, Univ. of California, Davis (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-17]

Bidirectional probabilistic hyper-graph matching method using Bayes theorem, Wanhyun Cho, Sunworl Kim, Sangcheol Park, Chonnam National Univ. (Korea, Republic of) . . . . . . . . . . . . . . . . . . . . . . [8304A-18]

SeamCrop for image retargeting, Johannes Kiess, Benjamin Guthier, StephanKopf,WolfgangEffelsberg,Univ.Mannheim(Germany)[8304A-19]

Collecting fingerprints for recognition using mobile phone cameras, BianYang,XueLi,ChristophBusch,GjøvikUniv.College (Norway) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-20]

Overview of potential forensic analysis of an Android smartphone, ReinerCreutzburg,KnutKröger,StefanSack,FachhochschuleBrandenburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-21]

Forensics of geodata collected by Apple iOS and Google Android in mobile devices,KnutKröger,ReinerCreutzburg,FachhochschuleBrandenburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-22]

Template-based mobile platform image processing training, David Akopian,SantoshChandanaGolagani,MoosaEsfahanian,TheUniv.ofTexas at San Antonio (United States) . . . . . . . . . . . . . . . . . . . . [8304A-23]

Combining associative computing and distributed arithmetic methods for efficient implementation of multiple inner products, David Guevorkian,TampereUniv.ofTechnology(Finland);PetriLiuha,TimoYli-Pietilä,NokiaResearchCtr.(Finland);KarenO.Egiazarian,TampereUniv.of Technology (Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-24]

Presentation of forensically interesting Microsoft XBox 360 console features,SilasLuttenberger,KnutKröger,ReinerCreutzburg,Fachhochschule Brandenburg (Germany) . . . . . . . . . . . . . . . . . [8304A-25]

Presentation of forensically interesting Sony Playstation 3 console features,KnutKröger,GunnarDaugs,ReinerCreutzburg,FachhochschuleBrandenburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-26]

Fast smartphone safety application prototyping using Nokia data gathering, Arsen Akopian, Consultant (United States) . . . . . . . [8304A-27]

A neural network-based approach for recognition of engraved and embossed labels on metallic parts, Amir Shirkhodaie, Vinod K. Bandaru, Tennessee State Univ. (United States) . . . . . . . . . . . . . . . . . . . [8304A-28]

Application of two-dimensional continuous wavelet transform in digital holographic microscopy to reconstruction of 3D rotational overview image of biological specimens, Victor Valenzuela Vermehren, Univ.doEstadodoAmazonas(Brazil);HelioMagalhãesdeOliveira,Univ.Federal de Pernambuco (Brazil) . . . . . . . . . . . . . . . . . . . . . . . . [8304A-29]

A fuzzy-logic approach for metallic parts surface defects characterization and shape classification, Amir Shirkhodaie, Fatemeh Vaziribozorg, Tennessee State Univ. (United States) . . . . . . . . [8304A-30]

Sudoku substitution-permutation image cipher, Yue Wu, Tufts Univ. (UnitedStates);SosAgaian,TheUniv.ofTexasatSanAntonio(UnitedStates);JosephP.Noonan,TuftsUniv.(UnitedStates) . . . . . . [8304A-31]



SESSION 1 . . . . . . . . . . . . . . . . . . . . .Wed. 9:30 to 10:30 am

Emerging Mobile ApplicationsSession Chairs: Reiner Creutzburg, Fachhochschule Brandenburg (Germany);David Akopian, The Univ. of Texas at San Antonio (United

States)

Location-aware gang graffiti acquisition and browsing on a mobile device,AlbertParraPozo,MireilleBoutin,EdwardJ.Delp,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-01]

Dietary intake assessment using integrated sensors and software, JunqingShang,EricJohnson,KishoreSundara-Rajan,AnkurTeredesai,Univ.ofWashington(UnitedStates);AlanKristal,FredHutchinsonCancerResearchCtr.(UnitedStates);AlexanderV.Mamishev,Univ.ofWashington (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-02]

FCam for multiple cameras (Invited Paper), Alejandro Troccoli, NVIDIA Corp.(UnitedStates);ChangyinZhou,ColumbiaUniv.(UnitedStates);KariPulli, NVIDIA Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . [8304A-03]


Processing and Displays for Mobile ApplicationsSession Chairs: Atanas P. Gotchev, Tampere Univ. of Technology (Finland);Reiner Creutzburg, Fachhochschule Brandenburg

(Germany)

Biosensing mobile display principle for healthcare,WallenMphepö,iVorexAB,Borlänge(Sweden)andBeijingNormalUniv.(China)[8304A-04]

Continuously adjustable Pulfrich spectacles for mobile devices, KennethM.Jacobs,BinghamtonUniv.(UnitedStates);RonaldS.Karpf,Consultant (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-05]

Parameters of the human 3D gaze while observing portable autostereoscopic display: a model and measurement results, Atanas R. Boev, Marianne Hanhela, Atanas P. Gotchev, Timo Utirainen, SatuJumisko-Pyykkö,TampereUniv.ofTechnology(Finland);MiskaHannuksela, Nokia Research Ctr. (Finland) . . . . . . . . . . . . . . . . [8304A-06]

Deblocking of mobile stereo video (Invited Paper), Atanas P. Gotchev, LucioAzzari,KarenO.Egiazarian,TampereUniv.ofTechnology( Finland) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-07]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pm

Security, Safety, and Location TechnologiesSession Chairs: David Akopian, The Univ. of Texas at San Antonio (UnitedStates);Namho Hur, ElectronicsandTelecommunications

Research Institute (Korea, Republic of)

SUPL support for mobile devices, Jayanthi M. Narisetty, Arpine Soghoyan, Mohanapriya C. Sundaramurthy, David Akopian, The Univ. of Texas at San Antonio (United States) . . . . . . . . . . . . . . . . . . . . [8304A-08]

Measuring ionizing radiation with a mobile device, Matthias Michelsburg,ThomasFehrenbach,FernandoPuenteLeón,KarlsruherInstitut für Technologie (Germany) . . . . . . . . . . . . . . . . . . . . . . [8304A-09]

Design and evaluation of security multimedia warnings for children’s smart phones, Jana Fruth, Sven Tuchscheerer, Otto-von-Guericke-Univ. Magdeburg (Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-10]

Using Wi-Fi hotspots as an intrusion vector into corporate networks, Maximilian Scharsich, Fachhochschule Brandenburg (Germany)[8304A-11]

SESSION 4 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pm

Algorithms for Mobile ComputingSession Chairs: Wanhyun Cho, Chonnam National Univ. (Korea, Republicof);David Akopian, The Univ. of Texas at San Antonio

(United States)

Frame rate up-conversion assisted with camera auto exposure information,LiangLiang,BobHung,GokceDane,QUALCOMMMEMSTechnologies, Inc. (United States). . . . . . . . . . . . . . . . . . . . . . . [8304A-12]

Fused Fibonacci-like (p,q) sequences with compression and barcoding applications, Sarkis Agaian, Jose Garcia, Salahodeen S. Abdul-Kafi, John T. Gill III, Stanford Univ. (United States) . . . . [8304A-13]

White synthesis with user input for color balancing on mobile camera systems,SatyamSrivastava,ChangXu,EdwardJ.DelpIII,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-14]

Detection and segmentation of symmetric shapes on a mobile device with applications to automatic sign interpretation (Invited Paper), AndrewW.Haddad,MireilleBoutin,EdwardJ.DelpIII,PurdueUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304A-15]

Conference8304A


Conference8304BMonday-Tuesday 23-24 January 2012 • Proceedings of SPIE Vol. 8304B

Multimedia Content Access: Algorithms and Systems VIConference Chairs: Cees G. M. Snoek, Univ.vanAmsterdam(Netherlands);Nicu Sebe, Univ.degliStudidiTrento(Italy);Lyndon Kennedy, Yahoo! Labs(UnitedStates)

Conference Co-Chairs: Theo Gevers, Univ.vanAmsterdam(Netherlands);Raimondo Schettini, Univ.degliStudidiMilano-Bicocca(Italy);Simone Santini, Univ. Autónoma de Madrid (Spain)

Program Committee: John Adcock, FXPaloAltoLab.(UnitedStates);Noboru Babaguchi, OsakaUniv.(Japan);Tat-Seng Chua, National Univ. of Singapore(Singapore);Matthew L. Cooper, FXPaloAltoLab.(UnitedStates);Francesco G. B. De Natale, Univ.degliStudidiTrento(Italy);Alberto Del Bimbo, Univ.degliStudidiFirenze(Italy);Jianping Fan, TheUniv.ofNorthCarolinaatCharlotte(UnitedStates);Yuli Gao, Hewlett-Packard Co. (UnitedStates);Alan Hanjalic, TechnischeUniv.Delft(Netherlands);Alexander G. Hauptmann, CarnegieMellonUniv.(UnitedStates);Winston H. Hsu, NationalTaiwanUniv.(Taiwan);Gang Hua, IBMThomasJ.WatsonResearchCtr.(UnitedStates);Xian-Sheng Hua, Microsoft Research Asia (China);Yu-Gang Jiang, ColumbiaUniv.(UnitedStates);Paul H. Lewis, Univ.ofSouthampton(UnitedKingdom);Rainer W. Lienhart, Univ. Augsburg (Germany);Vasileios Mezaris, InformaticsandTelematicsInstitute(Greece);Chong-Wah Ngo, CityUniv.ofHongKong(HongKong,China);Alan F. Smeaton, DublinCityUniv.(Ireland);John R. Smith, IBMThomasJ.WatsonResearchCtr.(UnitedStates);Hari Sundaram, Arizona State Univ. (UnitedStates);Qi Tian, TheUniv.ofTexasatSanAntonio(UnitedStates);Luc J. Van Gool, KatholiekeUniv.Leuven(Belgium);Dong Wang, Hulu (China);Meng Wang, MicrosoftResearchAsia(China);Changsheng Xu, InstituteofAutomation(China);Rong Yan, FacebookInc.(UnitedStates);Jun Yang, Facebook Inc. (United States)

Monday 23 JanuarySESSION 5 . . . . . . . . . . . . . . . . . . . . .Mon. 8:30 to 10:10 am

Multimedia Content ClassificationSession Chair: Cees G. M. Snoek, Univ. van Amsterdam (Netherlands)

Searching through photographic databases with QuickLook, Claudio Cusano, Gianluigi Ciocca, Raimondo Schettini, Univ. degli Studi di Milano-Bicocca(Italy);SimoneSantini,Univ.AutónomadeMadrid(Spain);AndreaDe Polo, Francesca Tavanti, Fratelli Alinari (Italy) . . . . . . . . . . . [8304B-32]

FSBMS: subject-based morph-show on Facebook, Marco Morana, RobertoGallea,MarcoLaCascia,Univ.degliStudidiPalermo (Italy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-33]

Large-scale classification of traffic signs under real-world conditions, LykeleHazelhoff,IvoM.Creusen,CycloMediaTechnologyB.V.(Netherlands);DennisVandeWouw,PeterH.N.deWith,TechnischeUniv.Eindhoven(Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-34]

Human action recognition using a Markovian conditional exponential model, Atulya Velivelli, Alexander G. Hauptmann, Carnegie Mellon Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-35]

Human activity discovery and recognition based on state transitions modeling in persistent surveillance systems, Amir Shirkhodaie, Vinayak Elangovan,TennesseeStateUniv.(UnitedStates) . . . . . . . . . . [8304B-36]

Keynote Presentation I . . . . . . . Mon. 10:50 to 11:50 amSession Chair: Lyndon S. Kennedy, Yahoo! Inc. (United States)

TBD, Trevor Darrell, Univ. of California, Berkeley (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-45]


Semantic Multimedia AccessSession Chair: Nicu Sebe, Univ. degli Studi di Trento (Italy)

Swimmer detection and pose estimation for continuous stroke-rate determination,DanZecha,ThomasGreif,RainerLienhart,Univ.Augsburg(Germany) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-37]

Multi-view face detection based on position estimation on multi-camera surveillance system, Ching-Chun Huang, National Kaohsiung Univ.ofAppliedSciences(Taiwan);JayChou,Jia-hauShiu,Sheng-JyhWang, National Chiao Tung Univ. (Taiwan) . . . . . . . . . . . . . . . . [8304B-38]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

Keynote Presentation II . . . . . . . . Mon. 2:00 to 3:00 pmSession Chair: Cees G. M. Snoek, Univ. van Amsterdam

(Netherlands)

TBD, Rong Yan, Facebook Inc. (United States) . . . . . . . . . . [8304B-46]

SESSION 7 . . . . . . . . . . . . . . . . . . . . . Mon. 3:00 to 5:00 pm

Bay Area MultimediaSession Chair: Lyndon S. Kennedy, Yahoo! Inc. (United States)

TBD, Radek Grzeszczuk, Nokia Research Ctr. (United States) [8304B-39]

TBD, George Toderici, Google Inc. (United States) . . . . . . . . . [8304B-40]

TBD,RoelofvanZwol,Yahoo!Inc.(UnitedStates) . . . . . . . . . [8304B-41]

TBD,QianLin,Hewlett-PackardLabs.(UnitedStates) . . . . . . [8304B-42]







Keyframe generation from cartoon animation using rule-based optical flow,PakpoomTanapichet,NagulCooharojananone,RajalidaLipikorn,Chulalongkorn Univ. (Thailand) . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-43]

Adaptive characterization, tracking, and semantic labeling of human-vehicle interactions via multimodality data fusion techniques, Amir Shirkhodaie,VinayakElangovan,TennesseeStateUniv.(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . [8304B-44]


Conference8304B


Conference 8305Tuesday-Thursday 24-26 January 2012 • Proceedings of SPIE Vol. 8305

Visual Information Processing and Communication IIIConference Chairs: Amir Said, Hewlett-PackardLabs.(UnitedStates);Onur G. Guleryuz, DoCoMoCommunicationsLabs.USA,Inc.(UnitedStates);Robert L. Stevenson, Univ. of Notre Dame (United States)

Program Committee: John G. Apostolopoulos, Hewlett-PackardLabs.(UnitedStates);Vasudev Bhaskaran, QualcommInc.(UnitedStates);Mireille Boutin, PurdueUniv.(UnitedStates);Chang Wen Chen, Univ.atBuffalo(UnitedStates);Gerard de Haan, Philips Research Nederland B.V.(Netherlands);Edward J. Delp III, PurdueUniv.(UnitedStates);Eric Dubois, Univ.ofOttawa(Canada);Frederic Dufaux, Telecom ParisTech (France);Touradj Ebrahimi, EcolePolytechniqueFédéraledeLausanne(Switzerland);Keigo Hirakawa, Univ.ofDayton(UnitedStates);Marta Karczewicz, QualcommInc.(UnitedStates);Janusz Konrad, BostonUniv.(UnitedStates);C.-C. Jay Kuo, The Univ. of Southern California (United States);Robert Paul Loce, XeroxCorp.(UnitedStates);Ligang Lu, IBMThomasJ.WatsonResearchCtr.(UnitedStates);Peyman Milanfar, Univ. ofCalifornia,SantaCruz(UnitedStates);Antonio Ortega, TheUniv.ofSouthernCalifornia(UnitedStates);Thrasyvoulos N. Pappas, Northwestern Univ.(UnitedStates);William A. Pearlman, RensselaerPolytechnicInstitute(UnitedStates);Fernando Pereira, Univ.TécnicadeLisboa(Portugal);Béatrice Pesquet-Popescu, TelecomParisTech(France);Majid Rabbani, EastmanKodakCo.(UnitedStates);Dan Schonfeld, Univ. of Illinois at Chicago(UnitedStates);Gaurav Sharma, Univ.ofRochester(UnitedStates);Andrew G. Tescher, AGTAssociates(UnitedStates);Anthony Vetro, MitsubishiElectricResearchLabs.(UnitedStates);John W. Woods, RensselaerPolytechnicInstitute(UnitedStates);Xiaolin Wu, McMaster Univ. (Canada)


Keynote Presentation I . . . . . . . . Tues. 9:30 to 10:30 amFor updated information, please visit www.spie.org/ei

SESSION 1 . . . . . . . . . . . . . . . . Tues. 11:10 am to 12:30 pmA novel distortion model for quadtree coding in high-efficiency video coding,BumshikLee,MunchurlKim,KAIST(Korea,Republicof) [8305-01]

Weighted prediction for HEVC, Philippe Bordes, Technicolor S.A. (France) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-02]

Impact of video parameters on the DCT coefficient distribution for H.264-like video coders, Nejat Kamaci, Ghassan Al-Regib, Georgia Institute of Technology (United States) . . . . . . . . . . . . . . . . . . . . .[8305-03]

Adaptive loop filter with directional similarity mapping for video coding,PoLinLai,FelixC.A.Fernandes,SAMSUNGTelecommunicationsAmerica Inc. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-04]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 2 . . . . . . . . . . . . . . . . . . . . . Tues. 2:00 to 3:20 pmDistributed video coding with progressive significance map, William A. Pearlman, Yang Hu, Rensselaer Polytechnic Institute (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-05]

Improving side information generation using dynamic motion estimation for distributed video coding, Insu Park, David W. Capson, McMaster Univ. (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-06]

Directional frame interpolation for MPEG compressed video, Chang Zhao,XinweiGao,XiaopengFan,DebinZhao,HarbinInstituteofTechnology (China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-07]

A fast intra-prediction method for high-efficiency video coding using Hadamard transform, Younhee Kim, George Mason Univ. (United States) andElectronicsandTelecommunicationsResearchInstitute(Korea,Republic of) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-08]

SESSION 3 . . . . . . . . . . . . . . . . . . . . . Tues. 4:00 to 5:20 pmLossless description of 3D range models, Neslihan Bayramoglu, A. AydinAlatan,MiddleEastTechnicalUniv.(Turkey) . . . . . . . . . . .[8305-09]

Reference frame selection for loss-resilient depth map coding in multiview video conferencing, Bruno Macchiavello, Camilo Dorea, MintsuHung,Univ.deBrasília(Brazil)andHewlettPackardLabs.(UnitedStates);GeneCheung,NationalInstituteofInformatics(Japan);Wai-TianTan,Hewlett-PackardLabs.(UnitedStates) . . . . . . . . . . . . . . . . .[8305-10]

Low-complexity automated depth-order estimation for 2D-to-3D video conversion, Robert Klepko, Communications Research Ctr. Canada (Canada) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-11]

Block-layer, optimal bit allocation based on constant perceptual quality,ChaoWang,XuanqinMou,Xi’anJiaotongUniv.(China);LeiZhang,TheHongKongPolytechnicUniv.(China) . . . . . . . . . . . .[8305-12]


Keynote Presentation II . . . . . . . Wed. 9:30 to 10:30 amFor updated information, please visit www.spie.org/ei

SESSION 4 . . . . . . . . . . . . . . . . Wed. 11:10 am to 12:30 pmPatch-wise ideal stopping time for anisotropic diffusion, Hossein Talebi Esfandarani,PeymanMilanfar,Univ.ofCalifornia,SantaCruz(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-13]

Video attention deviation estimation using inter-frame visual saliency map analysis, Yunlong Feng, Gene Cheung, National Institute of Informatics(Japan);PatrickLeCallet,Polytech’Nantes(France);YushengJi, National Institute of Informatics (Japan) . . . . . . . . . . . . . . . . . .[8305-14]

Robust grid registration for non-blind PSF estimation, Jonathan Simpkins,RobertL.Stevenson,Univ.ofNotreDame(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-15]

Fast pseudo-semantic segmentation for joint region-based hierarchical and multiresolution representation,RafiqSekkal,ClementStrauss, François Pasteau, Marie Babel, Olivier Déforges, Institut National desSciencesAppliquéesdeRennes(France) . . . . . . . . . . . . . . .[8305-16]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm


SESSION 5 . . . . . . . . . . . . . . . . . . . . . Wed. 2:00 to 3:20 pmOptimal local dimming for LED-backlit LCD displays via linear programming,XiaoShu,XiaolinWu,McMasterUniv.(Canada);SorenForchhammer, Technical Univ. of Denmark (Denmark) . . . . . . . .[8305-17]

Gestures for natural interaction with video,NesrineFourati,EmmanuelMarilly,Alcatel-LucentBellLabs.Villarceaux(France) . . . . . . . . .[8305-18]

Improving underwater visibility using vignetting correction, Ken Sooknanan, Anil Kokaram, Trinity College Dublin (Ireland) . . . . . .[8305-19]

Defect pixel interpolation for lossy compression of camera raw data, MichaelSchöberl,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany)andFraunhofer-InstitutfürIntegrierteSchaltungen(Germany);JoachimKeinert,Fraunhofer-InstitutfürIntegrierteSchaltungen(Germany);JürgenSeiler,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany);SiegfriedFoessel,Fraunhofer-InstitutfürIntegrierteSchaltungen(Germany);AndréKaup,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany) .[8305-20]

SESSION 6 . . . . . . . . . . . . . . . . . . . . . Wed. 4:00 to 5:20 pmCubic-panorama image dataset compression,SaeedSalehi,EricDubois, Univ. of Ottawa (Canada) . . . . . . . . . . . . . . . . . . . . . . . . .[8305-21]

Lossless halftone image compression using adaptive context template update, Sung-Bum Park, Dai-Woong Choi, Jae-Won Yoon, SamsungElectronicsCo.,Ltd.(Korea,Republicof) . . . . . . . . . . .[8305-22]

Simple and efficient lossless remote sensing image compression based on a new method of transformation, Farshid Sepehrband, Sharif Univ.ofTechnology(Iran,IslamicRepublicof);PedramGhamisi,K.N.ToosiUniv.ofTechnology(Iran,IslamicRepublicof);JeiranChupan,SharifUniv.of Technology (Iran, Islamic Republic of) . . . . . . . . . . . . . . . . . . .[8305-23]

GA-based hyperspectral image compression by using enhanced DPCM, Pedram Ghamisi, K.N.Toosi Univ. of Technology (Iran, Islamic Republicof);FarshidSepehrband,SharifUniv.ofTechnology(Iran,IslamicRepublicof);AliMohammadzadeh,MahmoudRezaSahebi,K.N.ToosiUniv. of Technology (Iran, Islamic Republic of) . . . . . . . . . . . . . . .[8305-24]

Thursday 26 JanuaryKeynote Presentation III . . . . . . Thurs. 9:00 to 10:00 am

For updated information, please visit www.spie.org/ei

SESSION 7 . . . . . . . . . . . . . . . . . . Thurs. 10:40 to 12:20 pmRecognition of sport players’ numbers using fast-color segmentation, CédricVerleysen,ChristopheDeVleeschouwer,Univ.CatholiquedeLouvain(Belgium) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-33]

On the use of clustering for resource allocation in wireless visual sensor networks,AngelikiV.Katsenou,LisimachosPaulKondi,KonstantinosE.Parsopoulos,Univ.ofIoannina(Greece). . . . . . .[8305-34]

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks, Katerina Pandremmenou,LisimachosPaulKondi,KonstantinosE.Parsopoulos,Univ. of Ioannina (Greece) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-35]

State-of-the-art lossy compression of Martian images via the CMA-ES evolution strategy, Frank W. Moore, Brendan Babb, Univ. of Alaska Anchorage(UnitedStates);ShawnAldridge,TheUniv.ofSouthernCalifornia(UnitedStates);MichaelR.Peterson,Univ.ofHawai’iatHilo(United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-36]

Spatially adaptive superresolution using the optimal recovery framework, Abdul Jabeer Shaik, Sergio D. Cabrera, The Univ. of Texas at ElPaso(UnitedStates) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-37]

Conference 8305

SESSION 8 . . . . . . . . . . . . . . . . . . . Thurs. 2:00 to 12:30 pmSurvey of imaging applications used in roadway transportation, Natesh Manikoth,ACS,AXeroxCo.(UnitedStates);RobertP.Loce,WenchengWu,EdgarBernal,XeroxCorp.(UnitedStates) . . . . . . . . . . . . . .[8305-31]

Compression of 2D navigation views with rotational and translational motion,DominicSpringer,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany);FranzSimmet,DieterNiederkorn,AudiAG(Germany);AndréKaup,Friedrich-Alexander-Univ.Erlangen-Nürnberg(Germany) .[8305-27]

A semi-automatic traffic sign detection, classification, and positioning system,IvoM.Creusen,LykeleHazelhoff,PeterH.N.deWith, CycloMedia Technology B.V. (Netherlands) and Technische Univ. Eindhoven(Netherlands) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-25]

Lunch Break . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12:30to2:00pm

SESSION 9 . . . . . . . . . . . . . . . . . . . . Thurs. 4:00 to 5:40 pmImage simulation for automatic license plate recognition, Raja Bala, YonghuiZhao,AaronBurry,VladimirKozitsky,XeroxCorp.(UnitedStates);CraigSaunders,XeroxResearchCtr.EuropeGrenoble(France) . . . [8305-32]

Traffic camera markup language (TCML), Yang Cai, Carnegie Mellon Univ. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-26]

Passive detection of heavily laden vehicles, Troy McKay, Carl Salvaggio, Philip S. Salvaggio, Jason Faulring, Donald M. McKeown, Rochester InstituteofTechnology(UnitedStates);AlfredJ.Garrett,DavidColeman,LarryKoffman,SavannahRiverNationalLab.(UnitedStates) . . .[8305-29]

Application of the SNoW machine learning paradigm to a set of transportation imaging problems, Peter Paul, Aaron Burry, Xerox Corp. (United States) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-30]

On-board side pedestrian detection for automotive active safety system,RuzhongCheng,YongZhao,Xin’anWang,JiayaoXu,ShaotingLv,PekingUniv.(China) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .[8305-28]


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Course Daily Schedule

3D Imaging, Interaction, and MeasurementSC060 Stereoscopic Display Application Issues (Merritt, Woods) 8:30 am to 5:30 pm, $525 / $635, p. 60

SC1047 Autostereoscopic and Holographic Display Technologies (Lee) 8:30 am to 12:30 pm, $300 / $355, p. 60

SC1046 Video Processing Techniques for 3D Television (Ho) 1:30 to 5:30 pm, $300 / $355, p. 61

SC1045 Evaluation Methodology for 2D and 3D Displays (de Ridder, Heynderickx) 1:30 to 5:30 pm, $300 / $355, p. 61

SC1029 DLP Projection Technology (Ramanath) 8:30 am to 12:30 pm, $300 / $355, p. 61

SC927 3D Imaging (Agam) 8:30 am to 12:30 pm, $300 / $355, p. 62

Digital Imaging Sensors and ApplicationsSC967 High Dynamic Range Imaging: Sensors and Architectures (Darmont) 8:30 am to 5:30 pm, $525 / $635, p. 64

SC1058 Image Quality and Evaluation of Cameras In Mobile Devices (Wüller, Matherson) 8:30 am to 5:30 pm, $525 / $635, p. 66

SC1021 Mobile Computational Photography (Pulli, Ahonen, Troccoli) 8:30 am to 5:30 pm, $525 / $635, p. 65

SC837 Multivariate Analysis of Imaging and Sensor Data (Bajorski) 8:30 am to 5:30 pm, $525 / $635, p. 66

SC965 Joint Design of Optics and Image Processing for Imaging Systems (Stork) 1:30 to 5:30 pm, $300 / $355, p. 67

SC504 Introduction to CCD and CMOS Imaging Sensors and Applications (Janesick) 8:30 am to 5:30 pm, $665 / $775, p. 64

SC1049 Objective and Subjective Image Quality Camera Benchmarking (Hornung, Eliasson, Phillips) 8:30 am to 5:30 pm, $525 / $635, p. 63

SC916 Digital Camera and Sensor Evaluation Using Photon Transfer (Janesick) 8:30 am to 5:30 pm, $580 / $690, p. 65

SC1048 Image Processing for Single-Sensor Imaging Devices (Battiato) 8:30 am to 12:30 pm, $300 / $355, p. 63

Image ProcessingSC837 Multivariate Analysis of Imaging and Sensor Data (Bajorski) 8:30 am to 5:30 pm, $525 / $635, p. 67


SC468 Image Enhancement, Deblurring and Super-Resolution (Rabbani) 8:30 am to 5:30 pm, $525 / $635, p. 68

SC965 Joint Design of Optics and Image Processing for Imaging Systems (Stork) 1:30 to 5:30 pm, $300 / $355, p. 69

SC967 High Dynamic Range Imaging: Sensors and Architectures (Darmont) 8:30 am to 5:30 pm, $525 / $635, p. 70


SC060 Stereoscopic Display Application Issues (Merritt, Woods) 8:30 am to 5:30 pm, $525 / $635, p. 72

SC1050 Perception and Cognition for Emerging Imaging Technologies (Rogowitz) 8:30 am to 12:30 pm, $300 / $355, p. 71


SC1015 Understanding and Interpreting Images (Rabbani) 1:30 to 5:30 pm, $300 / $355, p. 71



electronicimaging.org • TEL: +1 703 642 9090 • [email protected] 59


Course Daily Schedule

Imaging, Visualization, and PerceptionSC1045 Evaluation Methodology for 2D and 3D Displays (de Ridder, Heynderickx) 1:30 to 5:30 pm, $300 / $355, p. 73

SC1050 Perception and Cognition for Emerging Imaging Technologies (Rogowitz) 8:30 am to 12:30 pm, $300 / $355, p. 73


SC1029 DLP Projection Technology (Ramanath) 8:30 am to 12:30 pm, $300 / $355, p. 76




SC060 Stereoscopic Display Application Issues (Merritt, Woods) 8:30 am to 5:30 pm, $525 / $635, p. 74



SC1015 Understanding and Interpreting Images (Rabbani) 1:30 to 5:30 pm, $300 / $355, p. 76


Multimedia Processing and ApplicationsSC1058 Image Quality and Evaluation of Cameras In Mobile Devices (Wüller, Matherson) 8:30 am to 5:30 pm, $525 / $635, p. 79







Visual Information Processing and CommunicationSC468 Image Enhancement, Deblurring and Super-Resolution (Rabbani) 8:30 am to 5:30 pm, $525 / $635, p. 82




Courses

3D Imaging, Interaction, and Measurement

Stereoscopic Display Application Issues

SC060Course level: IntermediateCEU .65 $525 / $635 USD Sunday 8:30 am to 5:30 pm

When correctly implemented, stereoscopic 3D displays can provide signifi cant benefi ts in many areas, including endoscopy and other medical imaging, teleoperated vehicles and telemanipulators, CAD, molecular modeling, 3D computer graphics, 3D visualization, photo interpretation, video-based training, and entertainment. This course conveys a concrete understanding of basic principles and pitfalls that should be considered when setting up stereoscopic systems and producing stereoscopic content. The course will demonstrate a range of stereoscopic hardware and 3D imaging & display principles, outline the key issues in an ortho-stereoscopic video display setup, and show 3D video from a wide variety of applied stereoscopic imaging systems.

LEARNING OUTCOMESThis course will enable you to:• list critical human factors guidelines for stereoscopic display

confi guration and implementation • calculate optimal camera focal length, separation, display size, and

viewing distance to achieve a desired level of depth acuity • examine comfort limits for focus/fi xation mismatch and on-

screen parallax values as a function of focal length, separation, convergence, display size, and viewing-distance factors

• set up a large-screen stereo display system using AV equipment readily available at most conference sites, for 3D stills and for full-motion 3D video

• rank the often-overlooked side-benefi ts of stereoscopic displays that should be included in a cost/benefi t analysis for proposed 3D applications

• explain common pitfalls in designing tests to compare 2D vs. 3D displays

• calculate and demonstrate the distortions in perceived 3D space due to camera and display parameters

• design and set up an ortho-stereoscopic 3D imaging/display system • understand the projective geometry involved in stereoscopic

modeling • determine the problems, and the solutions, for converting

stereoscopic video across video standards such as NTSC and PAL • work with stereoscopic 3D video and stills -using analog and digital

methods of capture/fi lming, encoding, storage, format conversion, display, and publishing

• describe the trade-offs among currently available stereoscopic display system technologies and determine which will best match a particular application

• understand existing and developing stereoscopic standards

INTENDED AUDIENCEThis course is designed for engineers, scientists, and program managers who are using, or considering using, stereoscopic 3D displays in their applications. The solid background in stereoscopic system fundamentals, along with many examples of advanced 3D display applications, makes this course highly useful both for those who are new to stereoscopic 3D and also for those who want to advance their current understanding and utilization of stereoscopic systems.

INSTRUCTORSJohn Merritt is a 3D display systems consultant at The Merritt Group, Williamsburg, MA, USA with more than 25 years experience in the design and human-factors evaluation of stereoscopic video displays for telepresence and telerobotics, off-road mobility, unmanned vehicles, night vision devices, photo interpretation, scientifi c visualization, and medical imaging.Andrew Woods is a research engineer at Curtin University’s Centre for Marine Science and Technology in Perth, Western Australia. He has over 20 years of experience working on the design, application, and evaluation of stereoscopic technologies for teleoperation, industrial,and entertainment applications.

Autostereoscopic and Holographic Display Technologies

SC1047 NEWCourse level: IntroductoryCEU .35 $300 / $355 USD Sunday 8:30 am to 12:30 pm

This course explains basic principles of 3D display technologies that might come after the currently mass-commercialized glasses-type (stereoscopic) display. The lecture will start with 3D perception cues of humans and key human factor issues. Then, the principles and status of autostereoscopic 3D display technologies will be described. The coverage will include parallax barrier technology, lenticular lens systems with 3D/2D switchable lenses, mutiview and super-multiview systems, integral imaging, holography using spatial light modulators and see-through 3D display systems for augmented reality. Key concepts in related image processing techniques will also be clarifi ed.

LEARNING OUTCOMESThis course will enable you to:• describe depth cues that make humans feel 3D perception• explain the principles of main next-generation 3D display

technologies - parallax barrier type, lenticular lens type, multiview and super-multiview type, integral imaging, holography using electronic devices and see-through 3D display.

• identify advantages, disadvantages and key issues of the above technologies

• design parallax barrier and lenticular lens systems• construct images for mutiview and integral imaging systems• construct images for integral imaging (integral photography)• explain procedure of generating data for phase-type spatial light

modulators for 3D display

INTENDED AUDIENCEScientists, engineers, managers, graduate students or new comers who wish to learn more about how to design autostereoscopic and electro-holographic 3D display systems and generate 3D images for the systems. Undergraduate training in engineering or science is assumed.

INSTRUCTORByoungho Lee has been working on 3D display for 17 years. He received his PhD degree from UC Berkeley in 1993 and is a professor in Electrical Engineering of Seoul National University, Korea. He has been consulting major display industries and government organizations in Korea for 3D display technologies. Dr. Lee is a Fellow of both SPIE and OSA. Currently he is the chair of the Holography and Diffractive Optics Technical Group of OSA. He has received several honors including Scientist of the Month Award of Korea in September 2009 based on his work for integral imaging and digital holography.


Courses

Video Processing Techniques for 3D Television

SC1046 NEWCourse level: IntermediateCEU .35 $300 / $355 USD Sunday 1:30 to 5:30 pm

This course explains the basic principles and the state-of-the-art video processing techniques for 3DTV. After reviewing the current status of 3DTV research activities, we will cover several challenging issues of 3D video processing, such as camera calibration, image rectifi cation, illumination compensation, color correction, depth map estimation, multi-view video-plus-depth coding, and intermediate view synthesis at virtual viewpoints.

LEARNING OUTCOMESThis course will enable you to:• identify the main components of video processing systems and their

functional roles• estimate camera parameters for camera calibration before capturing

image/video data• analyze the captured data for image rectifi cation and illumination

compensation• apply image processing techniques for color correction and fi ltering• estimate depth map information from stereoscopic and multi-view

images• design a coding system to encode multi-view video-plus-depth data• synthesize intermediate views at virtual viewpoints• solve various challenging problems related to 3DTV

INTENDED AUDIENCEScientists, engineers, technicians, or managers who wish to learn more about 3DTV and related video processing techniques. Undergraduate training in engineering or science is assumed.

INSTRUCTORYo-Sung Ho has been developing video processing systems for digital TV and HDTV, fi rst at Philips Labs in New York and later at ETRI in Korea. He is currently a professor of Information and Communications Department at Gwangju Institute of Science and Technology (GIST) in Korea, and also a Director of Realistic Broadcasting Research Center at GIST. He gave several tutorial lectures at various international conferences, including the 3DTV Conference, the IEEE International Conference on Image Processing (ICIP), and the IEEE International Conference on Multimedia & Expo (ICME). He earned his Ph.D. degree in Electrical and Computer Engineering at the University of California, Santa Barbara. He has been an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT).

Evaluation Methodology for 2D and 3D Displays

SC1045 NEWCourse level: IntroductoryCEU .35 $300 / $355 USD Sunday 1:30 to 5:30 pm

The course starts with an historical perspective of image quality, including an introduction to the Image Quality Circle framework of Engeldrum. The main goal of the fi rst part of the course is to understand how to design reliable perception experiments for measuring image quality. To this end, the course provides an overview of evaluation methodologies and discusses common pitfalls. Consequently, the concept of image quality is extended towards concepts as naturalness and viewing experience.In the second part of the course, the focus is fully on 3D displays. This second part starts with the basics of depth perception. It then explains how to extend the Image Quality Circle framework by combining depth perception with image quality. Finally, the course ends with an extensive discussion on issues of visual discomfort, possibly occurring after prolonged viewing of 3D content.

LEARNING OUTCOMESThis course will enable you to:• explain the Image Quality Circle framework• choose the appropriate methodology for a perception experiment

and list the related consequences• select the appropriate stimuli and estimate the related consequences• select the appropriate dependent variable and estimate the related

consequences• describe depth perception• extend the Image Quality Circle framework for 3D• defi ne design rules for artifact-free 3D content• defi ne design rules for a comfortable 3D display

INTENDED AUDIENCEScientists, engineers, technicians, or managers who wish to learn about how to design perception experiments on image quality and viewing experience and/or want to understand reasons for visual discomfort on 3D displays. Undergraduate training in engineering or science is assumed.

INSTRUCTORSHuib de Ridder is full professor of Informational Ergonomics at Delft University of Technology (the Netherlands). From 1982 till 1998 he was affi liated with the Vision Group of the Institute for Perception Research (IPO), Eindhoven, The Netherlands, where his research focused on visual psychophysics, in particular the fundamentals of image quality metrics. In Delft he continued his research on human behaviour at both perceptual and cognitive level covering topics like user understanding (e.g., intention tracking, interaction with embedded intelligence, engagement), information presentation (e.g., picture perception, form perception, image quality) and vision-based gesture recognition.Ingrid Heynderickx is research fellow at Philips Research, part-time full professor at the Technical University of Delft (the Netherlands) and guest professor at the Southeast University in Nanjing (China). During the last decade she specialized in applied visual perception for displays and lighting, including image quality evaluation for 2D and 3D displays. Her research contributions have been awarded with a fellowship at SID and the National Friendship Award of China.

DLP Projection Technology

SC1029Course level: IntroductoryCEU .35 $300 / $355 USD Sunday 8:30 am to 12:30 pm

This course explains the principles of displaying images and video using a Digital Micromirror Device (DMD) in UHP lamp and solid-state illuminated systems. The course will begin with giving the audience an overview of colorimetry as it applies to DLP-based systems and the various nuances of a creating a display system based on three to fi ve color primaries. The audience will be given examples of single chip and three-chip systems walking them from electrical signals into the projector to photons out of the projector in both 2D and 3D displays. Examples will include three-chip systems used in DLP Cinema® projectors, color wheel- and lamp-based single chip projectors; LED- and LASER-based single chip projectors used in conventional projectors, televisions and Pico projectors.


Courses

LEARNING OUTCOMESThis course will enable you to:• determine the throughput of a DLP-based projector and use it to

create and understand lumen budgets• estimate the throughput of a color wheel- and lamp-based, and LED-

based systems• explain the role of a color wheel and the tradeoffs made in designing

them• describe how 3D displays are created using DMDs• explain the role of pulse width modulation to create smooth ramps

using binary displays• judge the power of using color sequential displays to create full-color

images• describe the key challenges with implementing DLP-based

projectors• be familiar with the technology behind DLP-based projectors in

cinema, television, front-projection and pico applications

INTENDED AUDIENCEScientists, engineers, technicians, or managers, who wish to learn more about how DLP-based projection displays are designed and operated. Undergraduate training in engineering or science is assumed.

INSTRUCTORRajeev Ramanath has been designing and developing DLP-based projection systems since he joined Texas Instruments DLP® Products in 2004. He has held various engineering roles in DLP® Products working with front projection, television, and pico projection products as an algorithm developer and a systems engineer. He has authored journal articles, book reviews, conference publications spanning the fi elds of color imaging, color science, image processing and pattern recognition. He earned a Ph.D. in Electrical Engineering from North Carolina State University in 2003 for work on developing a framework for object recognition using spectral and spatial information.

3D Imaging

SC927Course level: IntroductoryCEU .35 $300 / $355 USD Tuesday 8:30 am to 12:30 pm

The purpose of this course is to introduce algorithms for 3D structure inference from 2D images. In many applications, inferring 3D structure from 2D images can provide crucial sensing information. The course will begin by reviewing geometric image formation and mathematical concepts that are used to describe it, and then move to discuss algorithms for 3D model reconstruction.The problem of 3D model reconstruction is an inverse problem in which we need to infer 3D information based on incomplete (2D) observations. We will discuss reconstruction algorithms which utilize information from multiple views. Reconstruction requires the knowledge of some intrinsic and extrinsic camera parameters, and the establishment of correspondence between views. We will discuss algorithms for determining camera parameters (camera calibration) and for obtaining correspondence using epipolar constraints between views. The course will also introduce relevant 3D imaging software components available through the industry standard OpenCV library.

LEARNING OUTCOMESThis course will enable you to:• describe fundamental concepts in 3D imaging• develop algorithms for 3D model reconstruction from 2D images• incorporate camera calibration into your reconstructions• classify the limitations of reconstruction techniques• use industry standard tools for developing 3D imaging applications

INTENDED AUDIENCEEngineers, researchers, and software developers, who develop imaging applications and/or use camera sensors for inspection, control, and analysis. The course assumes basic working knowledge concerning matrices and vectors.

INSTRUCTORGady Agam is an Associate Professor of Computer Science at the Illinois Institute of Technology. He is the director of the Visual Computing Lab at IIT which focuses on imaging, geometric modeling, and graphics applications. He received his PhD degree from Ben-Gurion University in 1999.

Multivariate Analysis of Imaging and Sensor Data

SC837 NEWCourse level: IntermediateCEU .65 $525 / $635 USD Sunday 8:30 am to 5:30 pm

In this course, you will learn useful tools for the analysis of data on many variables (such as data on many spectral bands or on several responses observed in an experiment). You will identify the benefi ts of incorporating information from several variables as opposed to analyzing each variable separately. Through understanding the principles behind the analytical tools, you will be able to decide when these tools should or should not be used in practice. Many practical and useful examples of analyses of imaging data are included. The instructor will emphasize intuitive and geometric understanding of the introduced concepts. The topics covered include multivariate descriptive statistics, multivariate normal (Gaussian) distribution, multivariate confi dence intervals, confi dence regions, principal component analysis (PCA), canonical correlation analysis, discrimination and classifi cation (supervised learning), Fisher discrimination, and independent component analysis (ICA).

LEARNING OUTCOMESThis course will enable you to:• construct multivariate confi dence intervals and confi dence regions

that ensure a desired joint confi dence level• explain variability in your data using principal component analysis

(PCA)• judge when PCA should be used on the covariance or correlation

matrices• use canonical correlations to investigate correlations between two

sets of variables• construct discrimination procedures for characterizing several

populations based on multivariate data• create plots based on Fisher discriminants• explain the concept of independent component analysis (ICA) and its

relationship to PCA

INTENDED AUDIENCEThis course is intended for participants who want to gain better insight into their multivariate data. Participants are expected to have a basic knowledge of vector and matrix algebra as well as some basic univariate statistics.

INSTRUCTORPeter Bajorski is an Associate Professor of Statistics at the Rochester Institute of Technology. He teaches graduate courses in statistics including a course on Multivariate Statistics for Imaging Science. He also designs and teaches short courses in industry, with longer-term follow-up and consulting. He performs research in statistics and in hyperspectral imaging, and is author of the book Statistics for Imaging, Optics, and Photonics (Wiley, 2011).Course includes content from the recommended supplementary text Statistics for Imaging, Optics, and Photonics (Wiley, 2011) by Peter Bajorski. The text will be available for purchase at the bookstore onsite at Electronic Imaging.


Courses

Digital Imaging Sensors and Applications

Image Processing for Single-Sensor Imaging Devices

SC1048 NEWCourse level: IntermediateCEU .35 $300 / $355 USD Wednesday 8:30 am to 12:30 pm

In the last decade, multimedia devices (camcorders, PDAs, mobile phones) have been dramatically diffused. Moreover, the increasing of their computational performances combined with an higher storage capability permits them to elaborate large amount of data. In order to reduce their cost and complexity manufacturers place a color fi lter array (CFA) on top of a single image sensor, which is basically a monochromatic device, to capture color information of the true visual scene. Cameras make use of an electronic sensor (CCD/CMOS) to acquire the spatial variations in light intensity and then use image processing algorithms to reconstruct a color picture from the data provided by the sensor. This course presents the main algorithms involved in the single-sensor imaging devices pipeline describing also some advanced applications. Also an overview of the recent trends and evolution, just considering the updated literature in the fi eld will be provided.

LEARNING OUTCOMESThis course will enable you to:• describe operating single-sensor imaging systems for commercial

and scientifi c imaging applications• explain how imaging data are acquired and processed (demosaicing,

color calibration, etc.)• list specifi cations and requirements to select a specifi c algorithm for

your imaging application• recognize performance differences among imaging pipeline

technologies• assess how image/video signals are processed for optimum signal-

to-noise performance• become familiar with current and future imaging technologies and

applications

INTENDED AUDIENCEThis course is intended for those with a general computing background, and is interested in the topic of image processing. Students, researchers, and practicing engineers should all be able to benefi t from the general overview of the fi eld and the introduction of the most recent advances of the technology.

INSTRUCTORSebastiano Battiato received his Ph.D. in computer science and applied mathematics in 1999, and led the “Imaging” team at STMicroelectronics in Catania through 2003. He joined the Department of Mathematics and Computer Science at the University of Catania as assistant professor in 2004 and became associate professor in 2011. His research interests include image enhancement and processing, image coding, camera imaging technology and multimedia forensics. He has published more than 90 papers in international journals, conference proceedings and book chapters. He is a co-inventor of about 15 international patents, reviewer for several international journals, and has been regularly a member of numerous international conference committees. He is director (and co-founder) of the International Computer Vision Summer School (ICVSS), Sicily, Italy. He is a senior member of the IEEE.

Objective and Subjective Image Quality Camera Benchmarking

SC1049 NEWCourse level: AdvancedCEU .65 $525 / $635 USD Monday 8:30 am to 5:30 pm

This course explains methodologies to assess image quality of photographic still image or motion picture capture device. The course will go through all the major image quality attributes, the fl aws that degrade those attributes, their causes and consequences on subjective perception. One important goal of the course is to provide a clear understanding of all attributes, how they can be visually assessed in real life picture from many examples images, as well as the physical phenomenon that can degrade image quality.The course thoroughly explains subjective evaluation methodologies, then objective measurement methodologies relying on existing standards from ISO, I3A/CPIQ and beyond, with many practical examples; how objective measurement metrics are related to subjective perception, methods to correlate objective metrics with subjective perception; and how one can build a benchmarking protocol with objective measurements from a capture use case perspective (such as consumer, landscape, sports,...) to an output use case perspective (such as handheld display, HDTV, photobook,...).

LEARNING OUTCOMESThis course will enable you to:• identify defects that degrade image quality in natural images and

what component of the camera should/could be improved for better image quality

• build up an image quality lab and master measurement protocols• select best key components to build a camera (best sensor for a

given price, best ISP on the market,...)• judge the overall image quality of a camera• evaluate the impact various output use cases have on overall image

quality• compare the image quality of a set of cameras• defi ne subjective test plans and protocols• setup benchmarking protocols depending on use cases

INTENDED AUDIENCEImage scientists, engineers, or managers who wish to learn more about image quality and how to evaluate camera performance for various output use cases. A good understanding of imaging and how a camera works is assumed. Anyone involved in photographic or motion picture imaging will benefi t from this course.

INSTRUCTORSHervé Hornung has been working in computer graphics and image processing for over 15 years, for Ray Dream in California and Live Picture in France before joining DxO Labs. He has been working on Image Quality Evaluation for 6 years at DxO Labs where he is now Senior Project Manager running product development projects. Achievements at DxO Labs include delivering many new measurement capabilities to the DxO Analyzer image quality evaluation solution and publishing many performance measurements through a benchmark protocol available at www.dxomark.com. He has lead a workshop at Image Sensors Europe in 2011 titled Image quality, subjective and objective evaluation.Henrik Eliasson has over 10 years experience of imaging and optical systems design and characterization. He is currently working at Sony Ericsson, where he has been for the past 8 years. In his role as a Master Engineer in imaging, he is in charge of mobile phone camera image tuning, verifi cation and characterization as well as imaging systems modeling and simulations. He is also actively involved in international standardization work as a representative in the I3A CPIQ (Camera Image Quality) initiative as well as in the ISO TC42/WG18 committee. His academic background includes a Ph.D. in Physics from Göteborg University, Sweden, where he was studying the dynamics of glass-forming liquids.


Courses

Jonathan Phillips is a Principal Scientist at Kodak where he has been employed for 20 years. His focus has been on photographic quality, with an emphasis on psychophysical testing for both product development and fundamental perceptual studies. His broad experience has included image quality work with capture, display, and print technologies. He received the 2011 I3A Achievement Award for his work on camera phone image quality and is currently heading the revision of ISO 20462 - Psychophysical experimental methods for estimating image quality - Part 3: Quality ruler method. He completed his graduate work in color science in the Center for Imaging Science at Rochester Institute of Technology and his chemistry undergraduate at Wheaton College (IL).

High Dynamic Range Imaging: Sensors and Architectures


This course provides attendees with an intermediate knowledge of high dynamic range image sensors and techniques for industrial and non-industrial applications. The course describes various sensor and pixel architectures to achieve high dynamic range imaging as well as software approaches to make high dynamic range images out of lower dynamic range sensors or image sets. The course follows a mathematic approach to defi ne the amount of information that can be extracted from the image for each of the methods described. Some methods for automatic control of exposure and dynamic range of image sensors and other issues like color and glare will be introduced.

LEARNING OUTCOMESThis course will enable you to:• describe various approaches to achieve high dynamic range imaging• predict the behavior of a given sensor or architecture on a scene• specify the sensor or system requirements for a high dynamic range

application• classify a high dynamic range application into one of several standard

types

INTENDED AUDIENCEThis material is intended for anyone who needs to learn more about quantitative side of high dynamic range imaging. Optical engineers, electronic engineers and scientists will fi nd useful information for their next high dynamic range application.

INSTRUCTORArnaud Darmont is owner and CEO of Aphesa, a company founded in 2008 and specialized in image sensor consulting, the EMVA1288 standard and camera benchmarking. He holds a degree in Electronic Engineering from the University of Liège (Belgium). Prior to founding Aphesa, he worked for over 7 years in the fi eld of CMOS image sensors and high dynamic range imaging.

Introduction to CCD and CMOS Imaging Sensors and Applications

SC504Course level: IntroductoryCEU .65 $665 / $775 USD Monday 8:30 am to 5:30 pm

This course provides a review of general theory and operation for CCD and CMOS imaging technologies looking at the development and application statuses of both. Performance differences between CMOS and CCD imaging arrays are covered. Fundamental performance limits behind major sensor operations are presented in addition to image defects, shorts, device yield, popular chip foundries, chip cost; custom designed and off-the-shelf sensors. We discuss operation principles behind popular commercial and scientifi c CMOS pixel architectures, and various array readout schemes. We cover backside illuminated arrays for UV, EUV and x-ray applications; high QE frontside illuminated sensors; deep depletion CCDs, ultra large CMOS and CCD arrays; high speed/ low noise parallel readout sensors. We describe the photon transfer technique in measuring performance and calibrating camera and chip systems, and charge transfer mechanisms. We review correlated double sampling theory used to achieve low noise performance and conclude with a look at future research and development trends for each technology.

LEARNING OUTCOMESThis course will enable you to:• describe operating CMOS and CCD arrays and camera systems for

commercial and scientifi c imaging applications• explain how CCD and CMOS arrays are designed, fabricated, tested

and calibrated• know how to apply test methodologies and performance standards• list specifi cations and requirements to select a sensor for your

imaging application• recognize performance differences between CMOS and CCD

technologies • understand how video signals are processed for optimum signal-to-

noise performance• become familiar with current and future imaging technologies and

applications

INTENDED AUDIENCEThis course is for scientists, engineers, and managers involved with high performance CCD and CMOS imaging sensors and camera systems.

INSTRUCTORJames Janesick is currently the director of the CMOS advanced development group for Sarnoff Corporation. Previously he was with Conexant Systems Inc. developing CMOS imaging arrays for commercial applications. He was technology director of Pixel Vision, Inc. for fi ve years developing high speed backside illuminated CCDs for scientifi c and cinema cameras. Prior to this Janesick was with the Jet Propulsion Laboratory for 22 years where as group leader he designed scientifi c ground and fl ight based imaging systems. He has authored 75 publications and has contributed to many NASA Tech Briefs and patents for various CCD and CMOS innovations. Janesick received NASA medals for Exceptional Engineering Achievement (1982 and 1992) and was the recipient of the SPIE Educator Award (2004) and was SPIE /IS&T Imaging Scientist of the Year (2007).

COURSE PRICE INCLUDES the texts Scientifi c Charge Coupled Devices (SPIE Press, 2001), and Photon Transfer (SPIE Press, 2007) by James Janesick.


Courses

Digital Camera and Sensor Evaluation Using Photon Transfer


Photon transfer (PT) is a popular and essential characterization standard employed in the design, operation, characterization, calibration, optimization, specification and application of digital scientific and commercial camera systems. The PT user friendly technique is based on only two measurements- average signal and rms noise which together produce a multitude of important data products in evaluating digital camera systems (most notably CCD and CMOS). PT is applicable to all imaging disciplines. Design and fabrication process engineers developing imagers rely heavily on PT data products in determining discrete performance parameters such as quantum effi ciency (QE), quantum yield, read noise, full well, dynamic range, nonlinearity, fi xed pattern noise, V/e- conversion gain, dark current , image, etc.. Camera users routinely use the PT technique to determine system level performance parameters to convert relative measurements into absolute electron and photon units, offset correction, fl at fi eld and image S/N, ADC quantizing noise, optimum encoding, minimum detectable luminance, operating temperature to remove dark current , reliability, stability, etc. PT is also the fi rst go/no-go test performed to determine the health of new camera system and/or detector as well as provide a power tool in trouble shooting problems. This course will review these aspects and many others offered by PT.

LEARNING OUTCOMESThis course will enable you to:• describe PT theory• take PT data and determine important CCD and CMOS performance

parameters• show example PT data products generated by CCD and CMOS

imagers• calibrate a camera system in absolute physical units• use PT to determine the best camera or CCD/CMOS imager for the

application• use PT to demonstrate and verify the camera system is reliable and

in good operating order• discuss guidelines for the novice and advanced user in generating

PT, Modulation and Lux Transfer curves• use PT to optimally remove fi xed pattern noise sources in images for

the highest S/N possible through fl at fi elding• comprehend signal-to-noise image theory through PT

INTENDED AUDIENCEEngineers, scientists, and technical managers working with commercial and scientifi c digital camera systems. Some familiarity with CCD and CMOS imagers is recommended.

INSTRUCTORJames Janesick is currently the director of the CMOS advanced development group for Sarnoff Corporation. Previously he was with Conexant Systems Inc. developing CMOS imaging arrays for commercial applications. He was technology director of Pixel Vision, Inc. for fi ve years developing high speed backside illuminated CCDs for scientifi c and cinema cameras. Prior to this Janesick was with the Jet Propulsion Laboratory for 22 years where as group leader he designed scientifi c ground and fl ight based imaging systems. He has authored 75 publications and has contributed to many NASA Tech Briefs and patents for various CCD and CMOS innovations. Janesick received NASA medals for Exceptional Engineering Achievement (1982 and 1992) and was the recipient of the SPIE Educator Award (2004) and was SPIE /IS&T Imaging Scientist of the Year (2007).

COURSE PRICE INCLUDES the text Photon Transfer (SPIE Press, 2007) by James R. Janesick.

Mobile Computational Photography


This course explains mobile computational photography and how it differs from traditional off-line computational photography. In mobile computational photography the camera sensor, display, a computational unit, and devices (such as lens, flash, and sensors including accelerometers or gyroscopes) work jointly with a user in an interactive loop, where several images are taken quickly with changing camera parameters. A mobile computational photography system then creates in real- or near-real-time new images that extend the capabilities of a camera that takes a single image. Examples include high dynamic range (HDR) and panoramic photography. A key enabler is a new open-source camera control API, FCam, which allows precise control of a camera system, yet is easy to use and abstracts out details including synchronization of camera components such as the sensor, lens, and fl ash. The course covers several typical computational photography applications and explains how they can be implemented using FCam running on a camera phone such as Nokia N900 or on an NVIDIA Tegra development board. You will learn how to get started with FCam programming, as well as the structure and main components of FCamera, a sample implementation of a versatile mobile camera application, that can be extended to include your own computational photography applications.

LEARNING OUTCOMESThis course will enable you to:• explain main research topics in computational photography, and

how mobile computational photography differs from traditional computational photography

• describe the key components of FCam architecture for controlling computational cameras

• write computational photography applications on a camera phone using FCam for camera control; ARM CPU, Neon co-processor, and OpenGL ES 2.0 GPU for image processing

INTENDED AUDIENCEScientists and engineers who want do on-line computational photography on camera phones. Participants are expected to be able to understand C++ code.

INSTRUCTORSKari Pulli has worked over 20 years on visual computing, the last 12 years on mobile visual computing. He is a Senior Director of research at NVIDIA since April 2011, before that he was a Nokia Fellow at Nokia Research Center. He has previously organized and taught courses on mobile 3D graphics both at SIGGRAPH and Eurographics conferences, and has taught graphics and imaging at University of Oulu and Stanford University. He earned a PhD in computer science at University of Washington, Seattle, was a research associate at Stanford University, and a visiting scientist at MIT.Timo Ahonen received Ph.D. (with honors) in information engineering in 2009 from the University of Oulu, Finland, and is now a Senior Researcher at NRC Palo Alto. Currently he is working on computational photography on mobile devices. His research interests include computational photography, computer vision, object and face recognition, and image processing. He has authored several international journal and conference papers on texture feature extraction and its application in face image analysis and often reviews papers submitted to the major journals and conferences in computer vision. He visited ETH Zurich in 2002 and University of Maryland in 2005.


Courses

Alejandro Troccoli has been with NVIDIA since 2006 and joined NVIDIA Research as a Senior Research Scientist in March 2011 to work in mobile computer vision and applications. As a 3D Systems Software Engineer he lead the development of NVIDIA’s Optimus technology, contributed to NVIDIA’s hybrid technology and did development work for the Direct3D driver. Alejandro received a Licenciatura en Ciencias de la Computacion from the Universidad de Buenos Aires, Argentina in 2001. He did his graduate work at Columbia University in the City of New York, where he received a PhD in 2006.










relationship to PCA



Image Quality and Evaluation of Cameras In Mobile Devices


Digital and mobile imaging camera system performance is determined by a combination of sensor characteristics, lens characteristics, and image-processing algorithms. As pixel size decreases, sensitivity decreases and noise increases, requiring a more sophisticated noise-reduction algorithm to obtain good image quality. Furthermore, small pixels require high-resolution optics with low chromatic aberration and very small blur circles. Ultimately, there is a tradeoff between noise, resolution, sharpness, and the quality of an image.This short course provides an overview of “light in to byte out” issues associated with digital and mobile imaging cameras. The course covers, optics, sensors, image processing, and sources of noise in these cameras, algorithms to reduce it, and different methods of characterization. Although noise is typically measured as a standard deviation in a patch with uniform color, it does not always accurately represent human perception. Based on the “visual noise” algorithm described in ISO 15739, an improved approach for measuring noise as an image quality aspect will be demonstrated. The course shows a way to optimize image quality by balancing the tradeoff between noise and resolution. All methods discussed will use images as examples.

LEARNING OUTCOMESThis course will enable you to:• describe pixel technology and color fi ltering• describe illumination, photons, sensor and camera radiometry• select a sensor for a given application• describe and measure sensor performance metrics• describe and understand the optics of digital and mobile imaging

systems• examine the diffi culties in minimizing sensor sizes• assess the need for per unit calibrations in digital still cameras and

mobile imaging devices• learn about noise, its sources, and methods of managing it• make noise and resolution measurements based on international

standards - EMVA 1288 - ISO 14524 (OECF)/ISO 15739 (Noise) - Visual Noise - ISO 12233 (Resolution)• assess infl uence of the image pipeline on noise• utilize today’s algorithms to reduce noise in images• measure noise based on human perception• optimize image quality by balancing noise reduction and resolution• compare hardware tradeoffs, noise reduction algorithms, and

settings for optimal image quality

INTENDED AUDIENCEAll people evaluating the image quality of digital cameras, mobile cameras, and scanners would benefi t from participation. Technical staff of manufacturers, managers of digital imaging projects, as well as journalists and students studying image technology are among the intended audience.


CoursesINSTRUCTORSDietmar Wüller studied photographic sciences at the University of Cologne. He owns a test lab for digital photography and has been testing digital cameras and scanners for German magazines and manufacturers since 1997. He is the editor of the ISO scanner standards (ISO 21550 and ISO 16067) and the vice chairman of the photography section in the German DIN. He also chairs the digital photography working group in the European Color Initiative (ECI).Kevin Matherson is a senior image scientist in the research and development lab of Hewlett-Packard’s Imaging and Printing Group and has worked in the fi eld of digital imaging since 1985. He joined Hewlett Packard in 1996 and has participated in the development of all HP digital and mobile imaging cameras produced since that time. His primary research interests focus on noise characterization, optical system analysis, and the optimization of camera image quality. Dr. Matherson currently leads the camera characterization laboratory in Fort Collins and holds Masters and PhD degrees in Optical Sciences from the University of Arizona.

Joint Design of Optics and Image Processing for Imaging Systems

SC965Course level: IntroductoryCEU .35 $300 / $355 USD Sunday 1:30 to 5:30 pm

For centuries, optical imaging system design centered on exploiting the laws of the physics of light and materials (glass, plastic, refl ective metal, ...) to form high-quality (sharp, high-contrast, undistorted, ...) images that “looked good.” In the past several decades, the optical images produced by such systems have been ever more commonly sensed by digital detectors and the image imperfections corrected in software. The new era of electro-optical imaging offers a more fundamental revision to this paradigm, however: now the optics and image processing can be designed jointly to optimize an end-to-end digital merit function without regard to the traditional quality of the intermediate optical image. Many principles and guidelines from the optics-only era are counterproductive in the new era of electro-optical imaging and must be replaced by principles grounded on both the physics of photons and the information of bits.This short course will describe the theoretical and algorithmic foundations of new methods of jointly designing the optics and image processing of electro-optical imaging systems. The course will focus on the new concepts and approaches rather than commercial tools.

LEARNING OUTCOMESThis course will enable you to:• describe the basics of information theory• characterize electro-optical systems using linear systems theory• compute a predicted mean-squared error merit function• characterize the spatial statistics of sources• implement a Wiener fi lter• implement spatial convolution and digital fi ltering• make the distinction between traditional optics-only merit functions

and end-to-end digital merit functions• perform point-spread function engineering• become aware of the image processing implications of various

optical aberrations• describe wavefront coding and cubic phase plates• utilize the power of spherical coding• compare super-resolution algorithms and multi-aperture image

synthesizing systems• simulate the manufacturability of jointly designed imaging systems• evaluate new methods of electro-optical compensation

INTENDED AUDIENCEOptical designers familiar with system characterization (f#, depth of fi eld, numerical aperture, point spread functions, modulation transfer functions, ...) and image processing experts familiar with basic operations (convolution, digital sharpening, information theory, ...).

INSTRUCTORDavid Stork is Distinguished Research Scientist and Research Director at Rambus Labs, and a Fellow of the International Association for Pattern Recognition. He holds 40 US patents and has written nearly 200 technical publications including eight books or proceedings volumes such as Seeing the Light, Pattern Classifi cation (2nd ed.) and HAL’s Legacy. He has given over 230 technical presentations on computer image analysis of art in 19 countries.

Image Processing










relationship to PCA



Courses








standards - EMVA 1288 - ISO 14524 (OECF)/ISO 15739 (Noise) - Visual Noise - ISO 12233 (Resolution)• assess infl uence of the image pipeline on noise• utilize today’s algorithms to reduce noise in images• measure noise based on human perception• optimize image quality by balancing noise reduction and resolution• compare hardware tradeoffs, noise reduction algorithms, and settings

for optimal image quality


INSTRUCTORSDietmar Wüller studied photographic sciences at the University of Cologne. He owns a test lab for digital photography and has been testing digital cameras and scanners for German magazines and manufacturers since 1997. He is the editor of the ISO scanner standards (ISO 21550 and ISO 16067) and the vice chairman of the photography section in the German DIN. He also chairs the digital photography working group in the European Color Initiative (ECI).Kevin Matherson is a senior image scientist in the research and development lab of Hewlett-Packard’s Imaging and Printing Group and has worked in the fi eld of digital imaging since 1985. He joined Hewlett Packard in 1996 and has participated in the development of all HP digital and mobile imaging cameras produced since that time. His primary research interests focus on noise characterization, optical system analysis, and the optimization of camera image quality. Dr. Matherson currently leads the camera characterization laboratory in Fort Collins and holds Masters and PhD degrees in Optical Sciences from the University of Arizona.

Image Enhancement, Deblurring and Super-Resolution

SC468Course level: AdvancedCEU .65 $525 / $635 USD Sunday 8:30 am to 5:30 pm

This course discusses some of the advanced algorithms in the fi eld of digital image processing. In particular, it familiarizes the audience with the understanding, design, and implementation of advanced algorithms used in deblurring, contrast enhancement, sharpening, noise reduction, and super-resolution in still images and video. Some of the applications include medical imaging, entertainment imaging, consumer and professional digital still cameras/camcorders, forensic imaging, and surveillance. Many image examples complement the technical descriptions.

LEARNING OUTCOMESThis course will enable you to:• explain the various nonadaptive and adaptive techniques used

in image contrast enhancement. Examples include PhotoShop commands such as Brightness/Contrast, Auto Levels, Equalize and Shadow/Highlights, or Pizer’s technique and Moroney’s approach

• explain the fundamental techniques used in image Dynamic Range Compression (DRC).Illustrate using the fast bilateral fi ltering by Dorsey and Durand as an example.

• explain the various techniques used in image noise removal, such as bilateral fi ltering, sigma fi ltering and K-Nearest Neighbor

• explain the various techniques used in image sharpening such as nonlinear unsharp masking, etc.

• explain the basic techniques used in image deblurring (restoration) such as inverse fi ltering and Wiener fi ltering

• explain the fundamental ideas behind achieving image super-resolution from multiple lower resolution images of the same scene

• explain how motion information can be utilized in image sequences to improve the performance of various enhancement techniques such as noise removal, sharpening, and super-resolution

INTENDED AUDIENCEScientists, engineers, and managers who need to understand and/or apply the techniques employed in digital image processing in various products in a diverse set of applications such as medical imaging, professional and consumer imaging, forensic imaging, etc. Prior knowledge of digital fi ltering (convolution) is necessary for understanding the (Wiener fi ltering and inverse fi ltering) concepts used in deblurring (about 20% of the course content).


CoursesINSTRUCTORMajid Rabbani has 30 years of experience in digital imaging. He is a Kodak Fellow and Department Head and also an adjunct Associate Professor at Rochester Institute of Technology (RIT). He is the co-recipient of the 2005 and 1988 Kodak C. E. K. Mees Awards and the co-recipient of two Emmy Engineering Awards in 1990 and 1996. He is the co-author of the book “Digital Image Compression Techniques” published in 1991 and the creator of six video/CDROM courses in the area of digital imaging. Dr. Rabbani is a Fellow of SPIE, a Fellow of IEEE, and a Kodak Distinguished Inventor.

Joint Design of Optics and Image Processing for Imaging Systems

SC965Course level: IntroductoryCEU .35 $300 / $355 USD Sunday 1:30 to 5:30 pm

For centuries, optical imaging system design centered on exploiting the laws of the physics of light and materials (glass, plastic, refl ective metal, ...) to form high-quality (sharp, high-contrast, undistorted, ...) images that “looked good.” In the past several decades, the optical images produced by such systems have been ever more commonly sensed by digital detectors and the image imperfections corrected in software. The new era of electro-optical imaging offers a more fundamental revision to this paradigm, however: now the optics and image processing can be designed jointly to optimize an end-to-end digital merit function without regard to the traditional quality of the intermediate optical image. Many principles and guidelines from the optics-only era are counterproductive in the new era of electro-optical imaging and must be replaced by principles grounded on both the physics of photons and the information of bits.This short course will describe the theoretical and algorithmic foundations of new methods of jointly designing the optics and image processing of electro-optical imaging systems. The course will focus on the new concepts and approaches rather than commercial tools.

LEARNING OUTCOMESThis course will enable you to:• describe the basics of information theory• characterize electro-optical systems using linear systems theory• compute a predicted mean-squared error merit function• characterize the spatial statistics of sources• implement a Wiener fi lter• implement spatial convolution and digital fi ltering• make the distinction between traditional optics-only merit functions

and end-to-end digital merit functions• perform point-spread function engineering• become aware of the image processing implications of various

optical aberrations• describe wavefront coding and cubic phase plates• utilize the power of spherical coding• compare super-resolution algorithms and multi-aperture image

synthesizing systems• simulate the manufacturability of jointly designed imaging systems• evaluate new methods of electro-optical compensation

INTENDED AUDIENCEOptical designers familiar with system characterization (f#, depth of fi eld, numerical aperture, point spread functions, modulation transfer functions, ...) and image processing experts familiar with basic operations (convolution, digital sharpening, information theory, ...).

INSTRUCTORDavid Stork is Distinguished Research Scientist and Research Director at Rambus Labs, and a Fellow of the International Association for Pattern Recognition. He holds 40 US patents and has written nearly 200 technical publications including eight books or proceedings volumes such as Seeing the Light, Pattern Classifi cation (2nd ed.) and HAL’s Legacy. He has given over 230 technical presentations on computer image analysis of art in 19 countries.









INSTRUCTORSKari Pulli has worked over 20 years on visual computing, the last 12 years on mobile visual computing. He is a Senior Director of research at NVIDIA since April 2011, before that he was a Nokia Fellow at Nokia Research Center. He has previously organized and taught courses on mobile 3D graphics both at SIGGRAPH and Eurographics conferences, and has taught graphics and imaging at University of Oulu and Stanford University. He earned a PhD in computer science at University of Washington, Seattle, was a research associate at Stanford University, and a visiting scientist at MIT.


Timo Ahonen received Ph.D. (with honors) in information engineering in 2009 from the University of Oulu, Finland, and is now a Senior Researcher at NRC Palo Alto. Currently he is working on computational photography on mobile devices. His research interests include computational photography, computer vision, object and face recognition, and image processing. He has authored several international journal and conference papers on texture feature extraction and its application in face image analysis and often reviews papers submitted to the major journals and conferences in computer vision. He visited ETH Zurich in 2002 and University of Maryland in 2005.Alejandro Troccoli has been with NVIDIA since 2006 and joined NVIDIA Research as a Senior Research Scientist in March 2011 to work in mobile computer vision and applications. As a 3D Systems Software Engineer he lead the development of NVIDIA’s Optimus technology, contributed to NVIDIA’s hybrid technology and did development work for the Direct3D driver. Alejandro received a Licenciatura en Ciencias de la Computacion from the Universidad de Buenos Aires, Argentina in 2001. He did his graduate work at Columbia University in the City of New York, where he received a PhD in 2006.





application• classify a high dynamic range application into one of several

standard types












applications



Courses


Courses

Understanding and Interpreting Images

SC1015Course level: IntroductoryCEU .35 $300 / $355 USD Tuesday 1:30 to 5:30 pm

A key problem in computer vision is image and video understanding, which can be defi ned as the task of recognizing objects in the scene and their corresponding relationships and semantics, in addition to identifying the scene category itself. Image understanding technology has numerous applications among which are smart capture devices, intelligent image processing, semantic image search and retrieval, image/video utilization (e.g., ratings on quality, usefulness, etc.), security and surveillance, intelligent asset selection and targeted advertising.This tutorial provides an introduction to the theory and practice of image understanding algorithms by studying the various technologies that serve the three major components of a generalized IU system, namely, feature extraction and selection, machine learning tools used for classifi cation, and datasets and ground truth used for training the classifi ers. Following this general development, a few application examples are studied in more detail to gain insight into how these technologies are employed in a practical IU system. Applications include face detection, sky detection, image orientation detection, main subject detection, and content based image retrieval (CBIR). Furthermore, realtime demos including face detection and recognition, CBIR, and automatic zooming and cropping of images based on main-subject detection are provided.

LEARNING OUTCOMESThis course will enable you to:• learn the various applications of IU and the scope of its consumer

and commercial uses• explain the various technologies used in image feature extraction

such as global, block-based or region-based color histograms and moments, the “tiny” image, GIST, histogram of oriented gradients (HOG), scale-invariant feature transform (SIFT), speeded-up robust features (SURF), bag of words, etc.

• explain the various machine learning paradigms and the fundamental techniques used for classifi cation such as Bayesian classifi ers, linear support vector machines (SVM) and nonlinear kernels, boosting techniques (e.g., AdaBoost), k-nearest neighbors, .etc.

• explain the concepts used for classifi er evaluation such as false positives and negatives, true positives and negatives, confusion matrix, precision and recall, and receiver operating characteristics (ROC)

• explain the basic methods employed in generating and labeling datasets and ground truth and examples of various datasets such as CMU PIE dataset, Label Me dataset, Caltech 256 dataset, TrecVid, FERET dataset, and Pascal Visual Object Recognition

• explain the fundamental ideas employed in the IU algorithms used for face detection, material detection, image orientation, and a few others

• learn the importance of using context in IU tasks

INTENDED AUDIENCEScientists, engineers, and managers who need to familiarize themselves with IU technology and understand its performance limitations in a diverse set of products and applications. No specifi c prior knowledge is required except familiarity with general mathematical concepts such as the dot product of two vectors and basic image processing concepts such as histograms, fi ltering, gradients, etc.

INSTRUCTORMajid Rabbani has 30 years of experience in digital imaging. He is a Kodak Fellow and a Department Head at Eastman Kodak research laboratories and also an adjunct Associate Professor at Rochester Institute of Technology (RIT). He is the co-recipient of the 2005 and 1988 Kodak C. E. K. Mees Awards and the co-recipient of two Emmy Engineering Awards in 1990 and 1996. He is the co-author of the book “Digital Image Compression Techniques” published in 1991 and the creator of six video/CDROM courses in the area of digital imaging with SPIE. Dr. Rabbani is a Fellow of SPIE, a Fellow of IEEE, and a Kodak Distinguished Inventor.

Perception and Cognition for Emerging Imaging Technologies


Imaging, visualization and computer graphics provide visual representations of data in order to communicate, provide insight and enhance problem solving. The human observer actively processes these visual representations using perceptual and cognitive mechanisms that have evolved over millions of years. The goal of this tutorial is to provide an introduction to these processing mechanisms, and to show how this knowledge can guide the decisions we make about how to represent data visually, how we visually represent patterns and relationships in data, and how we can use human pattern recognition to extract features in the data. The course is organized into four sections:Light, the Eye, and the Brain: Visual stimulus, visual physiology, eye movements, and neural pathways.Visual Information Processing: Luminance, contrast, spatial resolution, and spatial frequency; temporal frequency and motion; color vision; and luminance vs. color resolution.Visual Cognition - Attention and Perceptual Organization: Color as a “pre-attentive” cue, eye movements and visual attention, fi nding patterns and features, and representing relationships.Applying Perceptual Knowledge to Imaging, Visualization and Computer Graphics: Visual data representation, color maps, semantics, fi nding features and relationships in data, and a framework for addressing visualization and visual analysis perceptually.

LEARNING OUTCOMESThis course will enable you to:• describe basic principles of spatial, temporal, and color processing

by the human visual system• explore basic cognitive processes, including visual attention and

semantics• develop skills in applying knowledge about human perception

and cognition to interactive visualization and computer graphics applications

INTENDED AUDIENCEScientists, engineers, technicians, or managers who are involved in the design, testing or evaluation of electronic imaging systems. Business managers responsible for innovation and new product development. Anyone interested in human perception and the evolution of electronic imaging applications.

INSTRUCTORBernice Rogowitz founded and co-chairs the SPIE/IS&T Conference on Human Vision and Electronic Imaging (HVEI) which is a multi-disciplinary forum for research on perceptual and cognitive issues in imaging systems. Dr. Rogowitz received her PhD from Columbia University in visual psychophysics, worked as a researcher and research manager at the IBM T.J. Watson Research Center for over 20 years. She recently created Visual Perspectives, a consulting company focused on vision, visualization, visual analysis and sensory interfaces. She has published over 60 technical papers and has over 12 patents on perceptually-based approaches to visualization, display technology, semantic image search, color, social networking, surveillance, and haptic interfaces. She is a Fellow of the SPIE, a Fellow of the IS&T, and a Senior Member of the IEEE.


3D Imaging


The purpose of this course is to introduce algorithms for 3D structure inference from 2D images. In many applications, inferring 3D structure from 2D images can provide crucial sensing information. The course will begin by reviewing geometric image formation and mathematical concepts that are used to describe it, and then move to discuss algorithms for 3D model reconstruction.The problem of 3D model reconstruction is an inverse problem in which we need to infer 3D information based on incomplete (2D) observations. We will discuss reconstruction algorithms which utilize information from multiple views. Reconstruction requires the knowledge of some intrinsic and extrinsic camera parameters, and the establishment of correspondence between views. We will discuss algorithms for determining camera parameters (camera calibration) and for obtaining correspondence using epipolar constraints between views. The course will also introduce relevant 3D imaging software components available through the industry standard OpenCV library.























Courses


Imaging, Visualization, and Perception

Perception and Cognition for Emerging Imaging Technologies


Imaging, visualization and computer graphics provide visual representations of data in order to communicate, provide insight and enhance problem solving. The human observer actively processes these visual representations using perceptual and cognitive mechanisms that have evolved over millions of years. The goal of this tutorial is to provide an introduction to these processing mechanisms, and to show how this knowledge can guide the decisions we make about how to represent data visually, how we visually represent patterns and relationships in data, and how we can use human pattern recognition to extract features in the data. The course is organized into four sections:Light, the Eye, and the Brain: Visual stimulus, visual physiology, eye movements, and neural pathways.Visual Information Processing: Luminance, contrast, spatial resolution, and spatial frequency; temporal frequency and motion; color vision; and luminance vs. color resolution.Visual Cognition - Attention and Perceptual Organization: Color as a “pre-attentive” cue, eye movements and visual attention, fi nding patterns and features, and representing relationships.Applying Perceptual Knowledge to Imaging, Visualization and Computer Graphics: Visual data representation, color maps, semantics, fi nding features and relationships in data, and a framework for addressing visualization and visual analysis perceptually.

LEARNING OUTCOMESThis course will enable you to:• describe basic principles of spatial, temporal, and color processing

by the human visual system• explore basic cognitive processes, including visual attention and

semantics• develop skills in applying knowledge about human perception

and cognition to interactive visualization and computer graphics applications

INTENDED AUDIENCEScientists, engineers, technicians, or managers who are involved in the design, testing or evaluation of electronic imaging systems. Business managers responsible for innovation and new product development. Anyone interested in human perception and the evolution of electronic imaging applications.

INSTRUCTORBernice Rogowitz founded and co-chairs the SPIE/IS&T Conference on Human Vision and Electronic Imaging (HVEI) which is a multi-disciplinary forum for research on perceptual and cognitive issues in imaging systems. Dr. Rogowitz received her PhD from Columbia University in visual psychophysics, worked as a researcher and research manager at the IBM T.J. Watson Research Center for over 20 years. She recently created Visual Perspectives, a consulting company focused on vision, visualization, visual analysis and sensory interfaces. She has published over 60 technical papers and has over 12 patents on perceptually-based approaches to visualization, display technology, semantic image search, color, social networking, surveillance, and haptic interfaces. She is a Fellow of the SPIE, a Fellow of the IS&T, and a Senior Member of the IEEE.

Evaluation Methodology for 2D and 3D Displays

SC1045 NEWCourse level: IntroductoryCEU .35 $300 / $355 USD Sunday 1:30 to 5:30 pm

The course starts with an historical perspective of image quality, including an introduction to the Image Quality Circle framework of Engeldrum. The main goal of the fi rst part of the course is to understand how to design reliable perception experiments for measuring image quality. To this end, the course provides an overview of evaluation methodologies and discusses common pitfalls. Consequently, the concept of image quality is extended towards concepts as naturalness and viewing experience.In the second part of the course, the focus is fully on 3D displays. This second part starts with the basics of depth perception. It then explains how to extend the Image Quality Circle framework by combining depth perception with image quality. Finally, the course ends with an extensive discussion on issues of visual discomfort, possibly occurring after prolonged viewing of 3D content.

LEARNING OUTCOMESThis course will enable you to:• explain the Image Quality Circle framework• choose the appropriate methodology for a perception experiment

and list the related consequences• select the appropriate stimuli and estimate the related consequences• select the appropriate dependent variable and estimate the related

consequences• describe depth perception• extend the Image Quality Circle framework for 3D• defi ne design rules for artifact-free 3D content• defi ne design rules for a comfortable 3D display

INTENDED AUDIENCEScientists, engineers, technicians, or managers who wish to learn about how to design perception experiments on image quality and viewing experience and/or want to understand reasons for visual discomfort on 3D displays. Undergraduate training in engineering or science is assumed.

INSTRUCTORSHuib de Ridder is full professor of Informational Ergonomics at Delft University of Technology (the Netherlands). From 1982 till 1998 he was affi liated with the Vision Group of the Institute for Perception Research (IPO), Eindhoven, The Netherlands, where his research focused on visual psychophysics, in particular the fundamentals of image quality metrics. In Delft he continued his research on human behaviour at both perceptual and cognitive level covering topics like user understanding (e.g., intention tracking, interaction with embedded intelligence, engagement), information presentation (e.g., picture perception, form perception, image quality) and vision-based gesture recognition.Ingrid Heynderickx is research fellow at Philips Research, part-time full professor at the Technical University of Delft (the Netherlands) and guest professor at the Southeast University in Nanjing (China). During the last decade she specialized in applied visual perception for displays and lighting, including image quality evaluation for 2D and 3D displays. Her research contributions have been awarded with a fellowship at SID and the National Friendship Award of China.

Courses

































INSTRUCTORMajid Rabbani has 30 years of experience in digital imaging. He is a Kodak Fellow and Department Head and also an adjunct Associate Professor at Rochester Institute of Technology (RIT). He is the co-recipient of the 2005 and 1988 Kodak C. E. K. Mees Awards and the co-recipient of two Emmy Engineering Awards in 1990 and 1996. He is the co-author of the book “Digital Image Compression Techniques” published in 1991 and the creator of six video/CDROM courses in the area of digital imaging. Dr. Rabbani is a Fellow of SPIE, a Fellow of IEEE, and a Kodak Distinguished Inventor.

Courses



SC837 NEW Course level: IntermediateCEU .65 $525 / $635 USD Sunday 8:30 am to 5:30 pm








relationship to PCA



3D Imaging


The purpose of this course is to introduce algorithms for 3D structure inference from 2D images. In many applications, inferring 3D structure from 2D images can provide crucial sensing information. The course will begin by reviewing geometric image formation and mathematical concepts that are used to describe it, and then move to discuss algorithms for 3D model reconstruction.

The problem of 3D model reconstruction is an inverse problem in which we need to infer 3D information based on incomplete (2D) observations. We will discuss reconstruction algorithms which utilize information from multiple views. Reconstruction requires the knowledge of some intrinsic and extrinsic camera parameters, and the establishment of correspondence between views. We will discuss algorithms for determining camera parameters (camera calibration) and for obtaining correspondence using epipolar constraints between views. The course will also introduce relevant 3D imaging software components available through the industry standard OpenCV library.









standard types



Courses


Understanding and Interpreting Images

SC1015Course level: IntroductoryCEU .35 $300 / $355 USD Tuesday 1:30 to 5:30 pm

A key problem in computer vision is image and video understanding, which can be defi ned as the task of recognizing objects in the scene and their corresponding relationships and semantics, in addition to identifying the scene category itself. Image understanding technology has numerous applications among which are smart capture devices, intelligent image processing, semantic image search and retrieval, image/video utilization (e.g., ratings on quality, usefulness, etc.), security and surveillance, intelligent asset selection and targeted advertising.This tutorial provides an introduction to the theory and practice of image understanding algorithms by studying the various technologies that serve the three major components of a generalized IU system, namely, feature extraction and selection, machine learning tools used for classifi cation, and datasets and ground truth used for training the classifi ers. Following this general development, a few application examples are studied in more detail to gain insight into how these technologies are employed in a practical IU system. Applications include face detection, sky detection, image orientation detection, main subject detection, and content based image retrieval (CBIR). Furthermore, realtime demos including face detection and recognition, CBIR, and automatic zooming and cropping of images based on main-subject detection are provided.

LEARNING OUTCOMESThis course will enable you to:• learn the various applications of IU and the scope of its consumer

and commercial uses• explain the various technologies used in image feature extraction

such as global, block-based or region-based color histograms and moments, the “tiny” image, GIST, histogram of oriented gradients (HOG), scale-invariant feature transform (SIFT), speeded-up robust features (SURF), bag of words, etc.

• explain the various machine learning paradigms and the fundamental techniques used for classifi cation such as Bayesian classifi ers, linear support vector machines (SVM) and nonlinear kernels, boosting techniques (e.g., AdaBoost), k-nearest neighbors, .etc.

• explain the concepts used for classifi er evaluation such as false positives and negatives, true positives and negatives, confusion matrix, precision and recall, and receiver operating characteristics (ROC)

• explain the basic methods employed in generating and labeling datasets and ground truth and examples of various datasets such as CMU PIE dataset, Label Me dataset, Caltech 256 dataset, TrecVid, FERET dataset, and Pascal Visual Object Recognition

• explain the fundamental ideas employed in the IU algorithms used for face detection, material detection, image orientation, and a few others

• learn the importance of using context in IU tasks

INTENDED AUDIENCEScientists, engineers, and managers who need to familiarize themselves with IU technology and understand its performance limitations in a diverse set of products and applications. No specifi c prior knowledge is required except familiarity with general mathematical concepts such as the dot product of two vectors and basic image processing concepts such as histograms, fi ltering, gradients, etc.

INSTRUCTORMajid Rabbani has 30 years of experience in digital imaging. He is a Kodak Fellow and a Department Head at Eastman Kodak research laboratories and also an adjunct Associate Professor at Rochester Institute of Technology (RIT). He is the co-recipient of the 2005 and 1988 Kodak C. E. K. Mees Awards and the co-recipient of two Emmy Engineering Awards in 1990 and 1996. He is the co-author of the book “Digital Image Compression Techniques” published in 1991 and the creator of six video/CDROM courses in the area of digital imaging with SPIE. Dr. Rabbani is a Fellow of SPIE, a Fellow of IEEE, and a Kodak Distinguished Inventor.

DLP Projection Technology


This course explains the principles of displaying images and video using a Digital Micromirror Device (DMD) in UHP lamp and solid-state illuminated systems. The course will begin with giving the audience an overview of colorimetry as it applies to DLP-based systems and the various nuances of a creating a display system based on three to fi ve color primaries. The audience will be given examples of single chip and three-chip systems walking them from electrical signals into the projector to photons out of the projector in both 2D and 3D displays. Examples will include three-chip systems used in DLP Cinema® projectors, color wheel- and lamp-based single chip projectors; LED- and LASER-based single chip projectors used in conventional projectors, televisions and Pico projectors.

LEARNING OUTCOMESThis course will enable you to:• determine the throughput of a DLP-based projector and use it to

create and understand lumen budgets• estimate the throughput of a color wheel- and lamp-based, and LED-

based systems• explain the role of a color wheel and the tradeoffs made in designing

them• describe how 3D displays are created using DMDs• explain the role of pulse width modulation to create smooth ramps

using binary displays• judge the power of using color sequential displays to create full-color

images• describe the key challenges with implementing DLP-based

projectors• be familiar with the technology behind DLP-based projectors in

cinema, television, front-projection and pico applications

INTENDED AUDIENCEScientists, engineers, technicians, or managers, who wish to learn more about how DLP-based projection displays are designed and operated. Undergraduate training in engineering or science is assumed.

INSTRUCTORRajeev Ramanath has been designing and developing DLP-based projection systems since he joined Texas Instruments DLP® Products in 2004. He has held various engineering roles in DLP® Products working with front projection, television, and pico projection products as an algorithm developer and a systems engineer. He has authored journal articles, book reviews, conference publications spanning the fi elds of color imaging, color science, image processing and pattern recognition. He earned a Ph.D. in Electrical Engineering from North Carolina State University in 2003 for work on developing a framework for object recognition using spectral and spatial information.

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applications












INSTRUCTORSHervé Hornung has been working in computer graphics and image processing for over 15 years, for Ray Dream in California and Live Picture in France before joining DxO Labs. He has been working on Image Quality Evaluation for 6 years at DxO Labs where he is now Senior Project Manager running product development projects. Achievements at DxO Labs include delivering many new measurement capabilities to the DxO Analyzer image quality evaluation solution and publishing many performance measurements through a benchmark protocol available at www.dxomark.com. He has lead a workshop at Image Sensors Europe in 2011 titled Image quality, subjective and objective evaluation.Henrik Eliasson has over 10 years experience of imaging and optical systems design and characterization. He is currently working at Sony Ericsson, where he has been for the past 8 years. In his role as a Master Engineer in imaging, he is in charge of mobile phone camera image tuning, verifi cation and characterization as well as imaging systems modeling and simulations. He is also actively involved in international standardization work as a representative in the I3A CPIQ (Camera Image Quality) initiative as well as in the ISO TC42/WG18 committee. His academic background includes a Ph.D. in Physics from Göteborg University, Sweden, where he was studying the dynamics of glass-forming liquids.

Courses


Jonathan Phillips is a Principal Scientist at Kodak where he has been employed for 20 years. His focus has been on photographic quality, with an emphasis on psychophysical testing for both product development and fundamental perceptual studies. His broad experience has included image quality work with capture, display, and print technologies. He received the 2011 I3A Achievement Award for his work on camera phone image quality and is currently heading the revision of ISO 20462 - Psychophysical experimental methods for estimating image quality - Part 3: Quality ruler method. He completed his graduate work in color science in the Center for Imaging Science at Rochester Institute of Technology and his chemistry undergraduate at Wheaton College (IL).







standardso EMVA 1288o ISO 14524 (OECF)/ISO 15739 (Noise)o Visual Noiseo ISO 12233 (Resolution)• assess infl uence of the image pipeline on noise• utilize today’s algorithms to reduce noise in images• measure noise based on human perception• optimize image quality by balancing noise reduction and resolution• compare hardware tradeoffs, noise reduction algorithms, and




Multimedia Processing and Applications




Courses







INSTRUCTORSKari Pulli has worked over 20 years on visual computing, the last 12 years on mobile visual computing. He is a Senior Director of research at NVIDIA since April 2011, before that he was a Nokia Fellow at Nokia Research Center. He has previously organized and taught courses on mobile 3D graphics both at SIGGRAPH and Eurographics conferences, and has taught graphics and imaging at University of Oulu and Stanford University. He earned a PhD in computer science at University of Washington, Seattle, was a research associate at Stanford University, and a visiting scientist at MIT.Timo Ahonen received Ph.D. (with honors) in information engineering in 2009 from the University of Oulu, Finland, and is now a Senior Researcher at NRC Palo Alto. Currently he is working on computational photography on mobile devices. His research interests include computational photography, computer vision, object and face recognition, and image processing. He has authored several international journal and conference papers on texture feature extraction and its application in face image analysis and often reviews papers submitted to the major journals and conferences in computer vision. He visited ETH Zurich in 2002 and University of Maryland in 2005.Alejandro Troccoli has been with NVIDIA since 2006 and joined NVIDIA Research as a Senior Research Scientist in March 2011 to work in mobile computer vision and applications. As a 3D Systems Software Engineer he lead the development of NVIDIA’s Optimus technology, contributed to NVIDIA’s hybrid technology and did development work for the Direct3D driver. Alejandro received a Licenciatura en Ciencias de la Computacion from the Universidad de Buenos Aires, Argentina in 2001. He did his graduate work at Columbia University in the City of New York, where he received a PhD in 2006.



Digital and mobile imaging camera system performance is determined by a combination of sensor characteristics, lens characteristics, and image-processing algorithms. As pixel size decreases, sensitivity decreases and noise increases, requiring a more sophisticated noise-reduction algorithm to obtain good image quality. Furthermore, small pixels require high-resolution optics with low chromatic aberration and very small blur circles. Ultimately, there is a tradeoff between noise, resolution, sharpness, and the quality of an image.

This short course provides an overview of “light in to byte out” issues associated with digital and mobile imaging cameras. The course covers, optics, sensors, image processing, and sources of noise in these cameras, algorithms to reduce it, and different methods of characterization. Although noise is typically measured as a standard deviation in a patch with uniform color, it does not always accurately represent human perception. Based on the “visual noise” algorithm described in ISO 15739, an improved approach for measuring noise as an image quality aspect will be demonstrated. The course shows a way to optimize image quality by balancing the tradeoff between noise and resolution. All methods discussed will use images as examples.








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standard types
























Courses













applications












Courses


INSTRUCTORSHervé Hornung has been working in computer graphics and image processing for over 15 years, for Ray Dream in California and Live Picture in France before joining DxO Labs. He has been working on Image Quality Evaluation for 6 years at DxO Labs where he is now Senior Project Manager running product development projects. Achievements at DxO Labs include delivering many new measurement capabilities to the DxO Analyzer image quality evaluation solution and publishing many performance measurements through a benchmark protocol available at www.dxomark.com. He has lead a workshop at Image Sensors Europe in 2011 titled Image quality, subjective and objective evaluation.Henrik Eliasson has over 10 years experience of imaging and optical systems design and characterization. He is currently working at Sony Ericsson, where he has been for the past 8 years. In his role as a Master Engineer in imaging, he is in charge of mobile phone camera image tuning, verifi cation and characterization as well as imaging systems modeling and simulations. He is also actively involved in international standardization work as a representative in the I3A CPIQ (Camera Image Quality) initiative as well as in the ISO TC42/WG18 committee. His academic background includes a Ph.D. in Physics from Göteborg University, Sweden, where he was studying the dynamics of glass-forming liquids.Jonathan Phillips is a Principal Scientist at Kodak where he has been employed for 20 years. His focus has been on photographic quality, with an emphasis on psychophysical testing for both product development and fundamental perceptual studies. His broad experience has included image quality work with capture, display, and print technologies. He received the 2011 I3A Achievement Award for his work on camera phone image quality and is currently heading the revision of ISO 20462 - Psychophysical experimental methods for estimating image quality - Part 3: Quality ruler method. He completed his graduate work in color science in the Center for Imaging Science at Rochester Institute of Technology and his chemistry undergraduate at Wheaton College (IL).

Visual Information Processing and Communication














Courses














Digital and mobile imaging camera system performance is determined by a combination of sensor characteristics, lens characteristics, and image-processing algorithms. As pixel size decreases, sensitivity decreases and noise increases, requiring a more sophisticated noise-reduction algorithm to obtain good image quality. Furthermore, small pixels require high-resolution optics with low chromatic aberration and very small blur circles. Ultimately, there is a tradeoff between noise, resolution, sharpness, and the quality of an image.

Courses

This short course provides an overview of “light in to byte out” issues associated with digital and mobile imaging cameras. The course covers, optics, sensors, image processing, and sources of noise in these cameras, algorithms to reduce it, and different methods of characterization. Although noise is typically measured as a standard deviation in a patch with uniform color, it does not always accurately represent human perception. Based on the “visual noise” algorithm described in ISO 15739, an improved approach for measuring noise as an image quality aspect will be demonstrated. The course shows a way to optimize image quality by balancing the tradeoff between noise and resolution. All methods discussed will use images as examples.









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Proceedings

Vol#Title(Editor)PrepublicationPrice

8288 Stereoscopic Displays and Applications XXIII (A.J.Woods/N.S.Holliman/G.E.Favalora) . . . . . . . . . . $120

8289 The Engineering Reality of Virtual Reality 2012 (I.E.McDowall/M.Dolinsky) . . . . . . . . . . . . . . . . . . . . . . . $53

8290 Three-Dimensional Image Processing (3DIP) and Applications II (A. M. Baskurt/R. Sitnik). . . . . . . . . . . . . . $80

8291 Human Vision and Electronic Imaging XVII(B.E.Rogowitz/T. N. Pappas/H. de Ridder) . . . . . . . . . . . . . . . $100

4 8292 Color Imaging XVII: Displaying, Processing, Hardcopy, and Applications(R.Eschbach/G.G.Marcu/A.Rizzi) . . $80

4 8293 Image Quality and System Performance IX (F. Gaykema/P. D. Burns). . . . . . . . . . . . . . . . . . . . . . . . . . $70

48294 Visualization and Data Analysis 2012 (P. C. Wong/D.L.Kao/M.C.Hao/C.Chen). . . . . . . . . . . . . . . . . . . . . . $70

8295 Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II (K.O.Egiazarian/S.S.Agaian/A.P.Gotchev/J.Recker/ G. Wang) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $90

8296 Computational Imaging X (C. A. Bouman/I. Pollak/P. J. Wolfe). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $60

4 8297 Document Recognition and Retrieval XIX (C.Viard-Gaudin/R.Zanibbi) . . . . . . . . . . . . . . . . . . . . . . . $60

8298 Sensors, Cameras, and Systems for Industrial and Scientific Applications XIII (R. Widenhorn/V. Nguyen/A. Dupret) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $60

4 8299 Digital Photography VIII (S. Battiato/B. G. Rodricks/N. Sampat) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $60

8300 Image Processing: Machine Vision Applications V (P.R.Bingham/E.Y.Lam) . . . . . . . . . . . . . . . . . . . . . . . . . $53

4 8301 Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques(J.Röning/D.P.Casasent). . . . . . . . . . . $70

8302 Imaging and Printing in a Web 2.0 World III (Q.Lin/J.P.Allebach/Z.Fan). . . . . . . . . . . . . . . . . . . . . . . . . . . . . $60

8303 Media Watermarking, Security, and Forensics IV (N.D.Memon/A.M.Alattar/E.J.DelpIII) . . . . . . . . . . . . . $53

8304 Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI (R. Creutzburg/D. Akopian/C. G. Snoek/N. Sebe/ L.Kennedy) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $70

4 8305 Visual Information Processing and Communication III (A.Said/O.G.Guleryuz/R.L.Stevenson) . . . . . . . . . . . . . $60

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Searchable CD with Multiple ConferencesCDs are now available within 8 weeks of the meeting.Full-text papers from all 18 Proceedings volumes.PC, Macintosh, and Unix compatible.

Electronic Imaging 2012(Includes Vols. 8288-8305)

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Order Proceedings volumes now and receive low prepublication prices.

ElectronicImaging

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22–26 January 2012


About the Symposium Organizers

IS&T, the Society for Imaging Science and Technology, is an international non-profit dedicated to keeping members and others apprised of the latest developments in fields related to imaging science through conferences, educational programs, publications, and its website. IS&T encompasses all aspects of imaging, with particular emphasis on digital printing, electronic imaging, color science, photofinishing, image preservation, silver halide, pre-press technology, and hybrid imaging systems.

IS&T offers members:

• Free,downloadableaccesstomorethan16,000 papers from IS&T conference proceedings via www.imaging.org

• ComplimentaryonlinesubscriptionstotheJournal of Imaging Science & Technology or the Journal of Electronic Imaging

• ReducedratesonIS&Tandotherpublications,including books, conference proceedings, and a second journal subscription.

• ReducedregistrationfeesatallIS&T sponsored or co-sponsored conferences—a valueequaltothedifferencebetweenmemberand non-member rates alone—as well as on conference short courses

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Contact IS&T for more information on these and other benefits.

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SPIEisaninternationalsocietyadvancinganinterdisciplinary approach to the science and applicationoflight.SPIEadvancesthegoalsof its Members, and the broader scientific community,inavarietyofways:

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• SPIEactsasacatalystforcollaborationamong technical disciplines, for information exchange, continuing education, publishing opportunities, patent precedent, and career and professional growth.

• SPIEisakeyorganizerandsponsorofmajor conferences, educational programs, and technical exhibitions on emerging technologiesaroundtheworld.SPIEmanages 25 to 30 events in North America, Europe,Asia,andtheSouthPacificannually;over40,000researchers,productdevelopers,and industry representatives participate in presenting, publishing, speaking, learning and networking opportunities.

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Documents

2012 Electronic Imaging - SPIE · 2011. 10. 26. · 22–26 January 2012 Hyatt Regency San Francisco Airport Hotel Burlingame, California, USA electronicimaging.org Advance Technical