Table of Contents

Volume I

Monday, October25th, 2004

SESSION MA-S1: Computational Radar Imaging

TIME-FREQUENCY BASED RADAR IMAGE FORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Victor Chen, US Naval Research Laboratory, USA

ISAR - RADAR IMAGING OF TARGETS WITH COMPLICATED MOTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Trygve Sparr, NDRE, Norway

A SURVEY ON ISAR AUTOFOCUSING TECHNIQUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9Fabrizio Berizzi, Marco Martorella, Dept. of Information Engineering, Italy; Brett Haywood, Defence Science &Technology Organization (DSTO), Australia; Enzo Dalle Mese and Silvia Bruscoli, Dept. of Information Engi-neering, Italy

SAR IMAGE FORMATION VIA INVERSION OF RADON TRANSFORMS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Nicholas Redding, DSTO, Australia

LONG INTEGRATION FINE RESOLUTION SAR IMAGE FORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Ngee Leng Tan and Sze Li Lee, DSO National Laboratories, Singapore

PERFORMANCE EVALUATION OF BACK-PROJECTION AND RANGE MIGRATION ALGORITHMS INFOLIAGE PENETRATION RADAR IMAGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Yibo Na, Hongbo Sun, Yee Hui Lee, Ling Chiat Tai and Hian Lim Chan, School of Electrical & Electronic Engi-neering, Nanyang Technological University, Singapore

DISTORTION IN THE INVERSE SYNTHETIC APERTURE RADAR IMAGES FROM MOVING TARGETS . 25S. K. Wong, G. Duff and E. Riseborough, Defence R&D, Canada

SESSION MA-L1: Watermarking I

QUANTITATIVE STEGANALYSIS OF BINARY IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Ming Jiang, Nasir Memon, Edward Wong, Polytechnic University, USA; and Xiaolin Wu, McMaster University,Canada

AUTHENTICATION OF MPEG-4 BASED SURVEILLANCE VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Michael Pramateftakis, Tobias Oelbaum and Klaus Diepold, Technische Universitaet Muenchen, Germany

ESTIMATING AND UNDOING ROTATION FOR PRINT-SCAN RESILIENT DATA HIDING . . . . . . . . . . . . . . . 39Kaushal Solanki, Upamanyu Madhow, B. S. Manjunath and Shiv Chandrasekaran, University of California atSanta Barbara, USA

RADON/RIDGELET SIGNATURE FOR IMAGE AUTHENTICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Zhen Yao and Nasir Rajpoot, Dept. of Computer Science, University of Warwick, UK

WATERMARKING OF 3D MODELS FOR DATA HIDING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47Petros Daras, Aristotle University of Thessaloniki, Greece; Dimitrios Zarpalas, Dimitrios Tzovaras, Informaticsand Telematics Institute, Greece; and Michael G. Strintzis, Aristotle University of Thessaloniki, Informatics andTelematics Institute, Greece

DATA HIDING IN CURVES FOR COLLUSION-RESISTANT DIGITAL FINGERPRINTING . . . . . . . . . . . . . . . . 51Hongmei Gou and Min Wu, University of Maryland, College Park, USA

ESTIMATION OF ATTACKER’S SCALE AND NOISE VARIANCE FOR QIM-DC WATERMARKEMBEDDING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55R. (Inald) L. Lagendijk and Ivo D. Shterev, Delft University of Technology, The Netherlands

DATA HIDING USING TRELLIS CODED QUANTIZATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Ersin Esen, TUBITAK Bilten, Turkey; and Aydin Alatan, Department of EE Engineering, METU, Turkey

SESSION MA-L2: Face Recognition

REGULARIZATION STUDIES ON LDA FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Juwei Lu, Konstantinos N. Plataniotis and Anastasios N. Venetsanopoulos, Bell Canada Multimedia Laboratory,The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Canada

A NOVEL PUPIL LOCALIZATION METHOD BASED ON GABOREYE MODEL AND RADIALSYMMETRY OPERATOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Peng Yang, Institute of Computing Technology of Chinese Academy of Sciences, China; Bo Du, Shiguang Shan,ICT-ISVISION Joint R&D Laboratory fo Face Recognition, China; and Wen Gao, Institute of Computing Technol-ogy of Chinese Academy of Sciences, China

FEATURE SELECTION FOR SUBJECT IDENTIFICATION IN SURVEILLANCE PHOTOS. . . . . . . . . . . . . . . . . 71Jie Wang, Konstantinos Plataniotis and Anastasios Venetsanopoulos, University of Toronto, Canada

ESTIMATING FACIAL POSE FROM SPARSE REPRESENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Hankyu Moon and Matt Miller, NEC Labs America, USA

FACE RECOGNITION USING RECURSIVE FISHER LINEAR DISCRIMINANT WITH GABOR WAVELETCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Cheng Xiang, Xiaoan Fan and TongHeng Lee, NUS, Singapore

A SUPERVISED NONLINEAR LOCAL EMBEDDING FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . 83Jian Cheng, Qingshan Liu, Hanqing Lu, Institute of Automation, Chinese Academy of Sciences, China; and Yen-Wei Chen, University of the Ryukyus, Japan

FUSION OF 2D AND 3D DATA IN THREE-DIMENSIONAL FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . 87Alexander Bronstein, Michael Bronstein, Eyal Gordon and Ron Kimmel, Technion - Israel Institute of Technology,Israel

POSE AND ILLUMINATION COMPENSATION FOR 3D FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . 91Sotiris Malassiotis and Michael Strintzis, Informatics and Telematics Institute, Greece

SESSION MA-L3: Video Compression Standards I

ADVANCED BLOCK SIZE SELECTION ALGORITHM FOR INTER FRAME CODING IN H.264/MPEG-4AVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95Andy C. Yu and Graham R. Martin, University of Warwick, UK

ROBUST VIDEO TRANSMISSION USING H.264 AND REAL-VALUED BCH FRAMES . . . . . . . . . . . . . . . . . . . 99Azza Ouled Zaid, Michel Kieffer, Chang-Ming Lee and Pierre Duhamel, LSS laboratory, France

VIDEO ENCODER COMPLEXITY REDUCTION BY ESTIMATING SKIP MODE DISTORTION . . . . . . . . . . . 103Iain Richardson and Yafan Zhao, The Robert Gordon University, UK

A NEW COLOR TRANSFORM FOR RGB CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Hyun Mun Kim, Woo-Shik Kim and Dae-Sung Cho, Samsung Advanced Institute of Technology, South Korea

RATE-DISTORTION-COMPLEXITY OPTIMIZATION OF FAST MOTION ESTIMATION IN H.264/MPEG-4AVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111Jesper Støttrup-Andersen, Milestone Systems A/S, Denmark; Søren Forchhammer, COM, Tech. Univ. Denmark,Denmark; and Shankar Manuel Aghito, COM, Technical University of Denmark, Denmark

FROM 8-TAP DCT TO 4-TAP INTEGER TRANSFORM FOR MPEG TO H.264/AVC TRANSCODING. . . . . . . 115Bo Shen, Hewlett-Packard Company, USA

FAST MODE DECISION FOR INTER PREDICTION IN H.264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Qionghai Dai, Dongdong Zhu and Rong Ding, ieee member, China

A LAGRANGIAN OPTIMIZED RATE CONTROL ALGORITHM FOR THE H.264/AVC ENCODER. . . . . . . . . 123M. Mahdi Ghandi and Mohammed Ghanbari, University of Essex, UK

SESSION MA-L4: Biomedical Image Processing: Segmentation andQuantitative Analysis

AN EVOLUTIONARY SNAKE ALGORITHM FOR THE SEGMENTATION OF NUCLEI INHISTOPATHOLOGICAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127Mohammed Ali Roula, Ahmed Bouridane and Fatih Kurugollu, Queen’s university of Belfast, UK

MULTIFRAME NONRIGID MOTION ANALYSIS WITH ANISOTROPIC SPATIAL CONSTRAINTS:APPLICATIONS TO CARDIAC IMAGE ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131Ken Wong, Huafeng Liu, Hong Kong University of Science and Technology, Hong Kong; Albert Sinusas, YaleUniversity, USA; and Pengcheng Shi, Hong Kong University of Science and Technology, Hong Kong

SEGMENTATION OF MICROSCOPE CELL IMAGES VIA ADAPTIVE EIGENFILTERS . . . . . . . . . . . . . . . . . . . 135Saravana Kumar, Sim Heng Ong, Surendra Ranganath, Fook Tim Chew and Tan Ching Ong, National Universityof Singapore, Singapore

DETECTION AND CLASSIFICATION OF BRIGHT LESIONS IN COLOR FUNDUS IMAGES . . . . . . . . . . . . . 139Xiaohui Zhang and Opas Chutatape, School of EEE, NTU, Singapore

EVALUATION OF SHADOW CLASSIFICATION TECHNIQUES FOR OBJECT DETECTION ANDTRACKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143John-Paul Renno, James Orwell and Graeme A Jones, Kingston University, UK

ADAPTIVE GATING IN GAUSSIAN BAYESIAN MULTI-TARGET TRACKING. . . . . . . . . . . . . . . . . . . . . . . . . . . 147Auguste Genovesio, Ziad Belhassine and Jean-Christophe Olivo-Marin, Institut Pasteur - Quantitative Image Anal-ysis, France

AUTOMATIC ASSESSMENT OF MAMMOGRAPHIC POSITIONING ON THE MEDIOLATERAL OBLIQUEVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151Sze Man Kwok, Ramachandran Chandrasekhar and Yianni Attikiouzel, Centre for Intelligent Information Process-ing Systems, Australia

LOCATING THE OPTIC DISK IN RETINAL IMAGES VIA PLAUSIBLE DETECTION AND CONSTRAINTSATISFACTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155Emanuele Trucco and Pawan Kamat, Heriot Watt University, UK

SESSION MA-L5: Error Resilience / Concealment I

A NEW FAMILY OF EMBEDDED MULTIPLE DESCRIPTION SCALAR QUANTIZERS . . . . . . . . . . . . . . . . . . . 159Augustin Ion Gavrilescu, Adrian Munteanu, Jean Cornelis and Peter Schelkens, Dept. of Electronics and Informa-tion Processing (ETRO), Belgium

ERROR RESILIENCE VIDEO CODING IN H.264 ENCODER WITH POTENTIAL DISTORTION TRACKING 163Yuan Zhang, Wen Gao, Chinese Academy of Sciences, China; Huifang Sun, Mitsubishi Electric Research Lab-oratories, USA; Qingming Huang, Chinese Academy of Sciences, China; and Yan Lu, Microsoft Research Asia,China

ERROR-PROPAGATION REDUCTION IN A BALANCED MULTIPLE DESCRIPTION VIDEO CODER . . . . . 167Marco Fumagalli, Cefriel - Politecnico di Milano, Italy; Nicola Franchi and Rosa Lancini, CEFRIEL, Italy

VISIBILITY OF INDIVIDUAL PACKET LOSSES IN MPEG-2 VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171Amy Reibman, AT&T Labs - Research, USA; Sandeep Kanumuri, UC San Diego, USA; Vinay Vaishampayan,AT&T Labs - Research, USA; and Pamela Cosman, UC San Diego, USA

MOTION COMPENSATED SHAPE ERROR CONCEALMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175Guido Schuster, University of Applied Sciences of Eastern Switzerland in Rapperswil, Switzerland; and AggelosKatsaggelos, Northwestern University, USA

A FLUID MODEL FOR ERROR PROPAGATION CHARACTERIZATION IN VIDEO CODING . . . . . . . . . . . . . 179Xiaoming Sun and C.-C. Jay Kuo, University of Southern California, USA

A GRADIENT BASED APPROACH FOR STEREOSCOPIC ERROR CONCEALMENT . . . . . . . . . . . . . . . . . . . . . 183Matthias Kunter, Sebastian Knorr, Carsten Clemens and Thomas Sikora, Technical University of Berlin, Germany

RECURSIVE DECODER DISTORTION ESTIMATION BASED ON AR(1) SOURCE MODELING FORVIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187Sila Ekmekci and Thomas Sikora, Technical University Berlin, Germany

SESSION MA-P1: Image Segmentation: By Color, Texture, and Edge

FAST FACE SEGMENTATION IN COMPONENT COLOR SPACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191Juan Jose De Dios, Universidad de Castilla-La Mancha, Spain; and Narciso Garcia, Universidad Politecnica deMadrid, Spain

COLOR SEGMENTATION OF INKED CHARACTERS : APPLICATION TO MEAT TRACEABILITYCONTROL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195Michele Gouiffes, Cemagref, France; Christine Fernandez-Maloigne, IRCOM SIC, Poitiers, France; AlainTremeau, LIGIV, St etienne, France; and Christophe Collewet, Cemagref, France

LEARNING SKIN DISTRIBUTION USING A SPARSE MAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199Rajkiran Gottumukkal, Old Dominion University, USA; and Vijayan Asari, Old Dominion Univeristy, USA

COLOR SPACE SELECTION FOR UNSUPERVISED COLOR IMAGE SEGMENTATION BY HISTOGRAMMULTITHRESHOLDING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203Laurent Busin, Nicolas Vandenbroucke, Ludovic Macaire and Jack-Gerard Postaire, Laboratoire LAGIS, France

ROBUST SKIN SEGMENTATION USING NEIGHBORHOOD INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207Javier Ruiz-del-Solar and Rodrigo Verschae, Universidad de Chile, Chile

PROPOSAL OF THE HYBRID SPECTRAL GRADIENT METHOD TO EXTRACT CHARACTER / TEXTREGIONS FROM GENERAL SCENE IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211Yoichiro Baba and Akira Hirose, The University of Tokyo, Japan

IMAGE SEGMENTATION BASED ON HIERARCHICAL MAPPING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215Apimun Junda and Orachat Chitsobhuk, Department of Computer Engineering, Faculty of Engineering, KingMongkut’s Institute of Technology Ladkrabang., Thailand

FEATURES EXTRACTION ON COMPLEX IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219Pierrick Bourgeat, Fabrice Meriaudeau, Patrick Gorria, Le2i Laboratory, France; Kenneth Tobin, Oak RidgeNational Laboratory, USA; and Frederick Truchetet, Le2i Laboratory, France

A SEMI-SUPERVISED SUPPORT VECTOR MACHINE FOR TEXTURE SEGMENTATION . . . . . . . . . . . . . . . . 223Saeid Sanei, King’s College London, UK; and Tracey Lee, National University of Singapore, Singapore

SCALE AND ROTATION INVARIANT TEXTURE FEATURES FROM THE DUAL-TREE COMPLEXWAVELET TRANSFORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227Edward Lo, Mark Pickering, Michael Frater and John Arnold, University College, The University of New SouthWales, Australia

SEGMENTATION OF OBJECT REGION USING DEPTH INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231Nak H. Kim and Jai Song Park, Hankuk Univ. of Foreign Studies, Korea

A 3-D CA-BASED EDGE OPERATOR FOR 3-D IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235Sartra Wongthanavasu, Khon Kaen University, Thailand; and Chidchanok Lursinsap, Chulalongkorn University,Thailand

TEXTURE CLASSIFICATION BASED ON SPATIAL DEPENDENCE FEATURES USINGCO-OCCURRENCE MATRICES AND MARKOV RANDOM FIELDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239William Schwartz and Helio Pedrini, Federal University of Parana - Computer Science Department, Brazil

SESSION MA-P2: Image Filtering and Morphological Processing

DEFECT DETECTION ON HARDWOOD LOGS USING HIGH RESOLUTION THREE-DIMENSIONALLASER SCAN DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243Liya Thomas, Lamine Mili, Clifford A. Shaffer, Virginia Polytechnic Institute and State University, USA; and EdThomas, USDA Forest Service Northeastern Research Station, USA

A ROBUST SPECKLE REDUCING ANISOTROPIC DIFFUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247Clovis Tauber, Hadj Batatia and Alain Ayache, ENSEEIHT-IRIT, France

EDGE DETECTION BASED ON DECISION-LEVEL INFORMATION FUSION AND ITS APPLICATION INHYBRID IMAGE FILTERING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251Jia Li, Oakland University, USA; and Xiaojun Jing, Beijing University of Posts and Telecommunications, China

ORDER FILTER WITH PROGRESSIVELY DECIMATED FILTERING WINDOW: APPLICATION TOCOLOUR IMAGE ENHANCEMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255Jocelyn Chanussot, Signal and Image Laboratory, Saint Martin D Heres, France

ACCELERATING SVD ON RECONFIGURABLE HARDWARE FOR IMAGE DENOISING. . . . . . . . . . . . . . . . . 259Aziz Ahmedsaid and Abbes Amira, Queens University Belfast, UK

IMAGE ENHANCEMENT USING STOCHASTIC RESONANCE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263Qinghua Ye, Haining Huang and Chunhua Zhang, Institute of Acoustics, Chinese Academy of Sciences, China

FILTERING OF COLOR MAP IMAGES BY CONTEXT TREE MODELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267Pavel Kopylov and Pasi Franti, University of Joensuu, Finland

TIKHONOV REGULARIZATION VERSUS SCALE SPACE: A NEW RESULT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271Luc Florack, Remco Duits and Joris Bierkens, Eindhoven University of Technology, The Netherlands

ESTIMATING THE PHASE CONGRUENCY OF LOCALISED FREQUENCIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275Peter Myerscough and Mark Nixon, Southampton University, UK

TEXTURE SEGMENTATION USING DIRECTIONAL EMPIRICAL MODE DECOMPOSITION . . . . . . . . . . . . 279Zhongxuan Liu, Hongjian Wang and Silong Peng, Institute of Automation, Chinease Academy of Sciences, China

A MATCHING METHOD BASED ON MARKER-CONTROLLED WATERSHED SEGMENTATION. . . . . . . . . 283Yi Hu and Tomoharu Nagao, Graduate School of Environment and Information Sciences, Yokohama NationalUniversity, Japan

H-THINNING FOR GRAY-SCALE IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287Sabrina Rami-Shojaei, Nestle research Center, Schwizerland; and Corinne Vachier, CMLA, ENS Cachan, France

SESSION MA-P3: Image Enhancement I

MOTION-BASED SPATIAL-TEMPORAL IMAGE REPAIRING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291Wen-Yi Zhao, Sarnoff Corporation, USA

TEMPORAL FILTERING OF WAVELET-COMPRESSED MOTION IMAGERY . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295Mark Robertson, AFRL Informtation Directorate/IFEC, USA

TWO LAYER SEGMENTATION FOR HANDLING PATHOLOGICAL MOTION IN DEGRADED POSTPRODUCTION MEDIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299Benjamin Kent, The Foundry, England; Anil Kokoram, Electronic and Electrical Engineering Department, Uni-versity of Dublin, Trinity College, Ireland; Bill Collis and Simon Robinson, The Foundry, England

OPTIMAL BLOCK BOUNDARY PRE/POST-FILTERING FOR WAVELET-BASED IMAGE AND VIDEOCOMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303Jie Liang, Simon Fraser University, Canada; Chengjie Tu, Microsoft, USA; and Trac Tran, Johns Hopkins Univer-sity, USA

A FILTERING APPROACH TO EDGE PRESERVING MAP ESTIMATION OF IMAGES . . . . . . . . . . . . . . . . . . . . 307David Humphrey and David Taubman, University of NSW, Australia

JOINT BLIND SEPARATION AND RESTORATION OF MIXED DEGRADED IMAGES FOR DOCUMENTANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311Anna Tonazzini, Istituto di Scienza e Tecnologie dell Informazione - Consiglio Nazionale delle Ricerche (Italy),Italy; Ivan Gerace and Francesco Cricco, Dipartimento di Matematica e Informatica - Universita degli Studi diPerugia, Italy

DESENSITISATION OF MEDICAL IMAGES RESTORATION UNDER CRUDE ESTIMATES OF MOBILERADIO CHANNELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315Guillermo Cisneros, Polytechnic University of Madrid, Spain; Emiliano Bernues, University of Zaragoza, Spain;Irma Rodrıguez, Miguel ngel Santiago and Federico lvarez, Polytechnic University of Madrid, Spain

ESTIMATING FIRST-ORDER FINITE-DIFFERENCE INFORMATION IN IMAGE RESTORATIONPROBLEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321Patrick L. Combettes, Universite Paris 6, France; and Jean-Christophe Pesquet, Universite Marne la Vallee,France

RESTORATION OF HALFTONED COLOR-QUANTIZED IMAGES USING PROJECTION ONTO CONVEXSETS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325Yik-Hing Fung and Yuk-Hee Chan, The Hong Kong Polytechnic University, Hong Kong

PERCEPTUAL IMAGE QUALITY ASSESSMENT BASED ON BAYESIAN NETWORKS . . . . . . . . . . . . . . . . . . 329Ronaldo Zampolo and Rui Seara, Federal University of Santa Catarina, Brazil

RECOGNITION OF PARTLY OCCLUDED PERSON ACTIONS IN MEETING SCENARIOS . . . . . . . . . . . . . . . . 333Martin Zobl, Andreas Laika, Frank Wallhoff and Gerhard Rigoll, Munich University of Technology, Institute forhuman-machine communication, Germany

SESSION MA-P4: Video Segmentation

ADAPTIVE SEGMENTATION FOR GYMNASTIC EXERCISES BASED ON CHANGE DETECTION OVERMULTIRESOLUTION COMBINED DIFFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337Jose M. Cobo, Luis Salgado and Julian Cabrera, Universidad Politecnica de Madrid, Spain

A KNOWLEDGE-BASED APPROACH TO DOMAIN-SPECIFIC COMPRESSED VIDEO ANALYSIS . . . . . . . 341Vasileios Mezaris, Ioannis Kompatsiaris and Michael Strintzis, Informatics and Telematics Institute, Centre forResearch and Technology Hellas, Greece

ANNOYANCE OF SPATIO-TEMPORAL ARTIFACTS IN SEGMENTATION QUALITY ASSESSMENT . . . . . 345Elisa Drelie Gelasca, Touradj Ebrahimi, EPFL - Swiss Federal Institute of Technology, Switzerland; Mylene C. Q.Farias, Marco Carli and Sanjit Mitra, Univerisity of California Santa Barbara, USA

HUMAN DETECTION IN GROUPS USING A FAST MEAN SHIFT PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . . . 349Csaba Beleznai, Advanced Computer Vision GmbH - ACV, Austria; Bernhard Fruhstuck, Siemens AG Austria,Austria; and Horst Bischof, Institute for Computer Graphics and Vision, Univ. of Technology Graz, Austria

A PROBABILISTIC FRAMEWORK FOR SEGMENTATION AND TRACKING OF MULTIPLE NON RIGIDOBJECTS FOR VIDEO SURVEILLANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353Aleksandar Ivanovic and Thomas S. Huang, Beckman Institute for Advanced Science and Technology, Universityof Illinois, USA

TEMPORAL STABILIZATION OF VIDEO OBJECT SEGMENTATION FOR 3D-TV APPLICATIONS . . . . . . . 357Cigdem Eroglu Erdem, Momentum A.S., Turkey; Fabian Ernst, Andre Redert, Philips Research Laboratories, TheNetherlands; and Emile Hendriks, Delft University of Technology, The Netherlands

INTEGRATION OF MOTION AND IMAGE FEATURES FOR AUTOMATIC VIDEO OBJECTSEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361Wei Wei and Ngan King Ngi, Department of Electronic Engineering, The Chinese University of Hong Kong, China

MOTION ESTIMATION AND DETECTION OF COMPLEX OBJECT BY ANALYZING RESAMPLEDMOVEMENTS OF PARTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365Punpiti Piamsa-nga, Kasetsart University, Thailand; and Noboru Babaguchi, Osaka University, Japan

MULTIPLE MOTION SEGMENTATION WITH LEVEL SETS WITHOUT PRIOR INFORMATION. . . . . . . . . . 369Olfa Besbes, Centre d’Etudes et de Recherche des Telecommunications, Tunisia; and Ziad Belhadj, EcoleSuperieure des Communications de Tunis, Tunisia

LV CONTOUR TRACKING IN MRI SEQUENCES BASED ON THE GENERALIZED FUZZY GVF . . . . . . . . . 373Wufan Chen, Shoujun Zhou, Key Lab for Medical Image Processing, Dept. of BME, the First Military MedicalUniv., China; and Bin Liang, Guang Dong Branch of NSBC, China

FAST MOTION ESTIMATION AND MOTION SEGMENTATION USING MULTI-SCALE APPROACH . . . . . 377Cedric Demonceaux, CREA/LAMFA, France; and Djemaa Kachi-Akkouche, CREA, France

A MOTION FIELD RECONSTRUCTION SCHEME FOR SMOOTH BOUNDARY VIDEO OBJECTSEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381Jean Gao, Ninad Thakoor and Sungyong Jung, University of Texas, USA

TEMPORAL VIDEO SEGMENTATION USING GLOBAL MOTION ESTIMATION AND DISCRETE CURVEEVOLUTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385Siripong Treetasanatavorn, Joerg Heuer, Uwe Rauschenbach, Siemens AG CT IC 2, Germany; Andre Kaup, Uni-versity of Erlangen-Nuremberg, Chair of Multimedia Communications and Signal Processing, Germany; andKlaus Illgner, Siemens AG CT IC 2, Germany

SESSION MA-P5: Low-level Image Indexing and Retrieval

USING MULTISCALE TOP POINTS IN IMAGE MATCHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389Bram Platel, Luc Florack, Frans Kanters and Evguenia Balmachnova, Technische Universiteit Eindhoven, TheNetherlands

ROTATION INVARIANT TEXTURE FEATURES USING ROTATED COMPLEX WAVELET FOR CONTENTBASED IMAGE RETRIEVAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393Manesh Kokare, P. K. Biswas and B. N. Chatterji, Indian Institute of Technology Kharagpur, India

A FRAMEWORK FOR SOFT HASHING AND ITS APPLICATION TO ROBUST IMAGE HASHING . . . . . . . . 397Elizabeth McCarthy, Felix Balado, Guenole Silvestre and Neil Hurley, University College Dublin, Ireland

COMBINING LOCAL CLASS PATTERNS AND DISCOVERED SEMANTICS FOR IMAGE RETRIEVAL . . . 401Joo-Hwee Lim, Institute for Infocomm Research, Singapore; and Jesse Jin, University of New South Wales, Aus-tralia

IMAGE RETRIEVAL BASED ON PROJECTIVE INVARIANCE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405Subhasis Chaudhuri, Vinay. P. Namboodiri, IIT Mumbai, India; and Rajashekhar S., IIT, Mumbai, India

A NOVEL 2D SHAPE MATCHING ALGORITHM BASED ON B-SPLINE MODELING . . . . . . . . . . . . . . . . . . . . 409Wang Yue and Teoh Eam Khwang, Nanyang Technological University, Singapore

CVPIC IMAGE RETRIEVAL BASED ON BLOCK COLOUR CO-OCCURANCE MATRIX AND PATTERNHISTOGRAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413Gerald Schaefer, Simon Lieutaud, Nottingham Trent University, UK; and Guoping Qiu, University of Nottingham,UK

SYMMETRY FEATURE IN CONTENT-BASED IMAGE RETRIEVAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417Jingrui He, Tsinghua University, China; Mingjing Li, Hongjiang Zhang, Microsoft Research Asia, China; andChangshui Zhang, Tsinghua University, China

REGION CORRESPONDENCE FOR IMAGE RETRIEVAL USING GRAPH-THEORETIC APPROACH ANDMAXIMUM LIKELIHOOD ESTIMATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421Chuech-Yu Li and Chiou-Ting Hsu, National Tsing Hua University, Taiwan

EFFICIENT IMAGE CODING FOR ACCESS TO PIXEL RANGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425Sehoon Yea, Rensselaer Polytechnic Institute, USA; Amir Said, Hewlett Packard Laboratories, USA; and WilliamPearlman, Rensselaer Polytechnic Institute, USA

COMPRESSED DOMAIN FEATURE TRANSFORMATION USING EVOLUTIONARY STRATEGIES FORfIMAGE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429Chun Ip Chiu, Hau San Wong and Horace H S Ip, Department of Computer Science, City University of Hong Kong,Hong Kong

IMAGE DATABASE RETRIEVAL USING SKETCHED QUERIES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433Abdolah Chalechale, Golshah Naghdy and Prashan Premaratne, University of Wollongong, Australia

JPEG2000 VS. JPEG FROM AN IMAGE RETRIEVAL POINT OF VIEW. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437Gerald Schaefer, Nottingham Trent University, UK

SESSION MA-P6: DCT-based Video Coding

A VIDEO CODING SYSTEM FOR SIGN LANGUAGE COMMUNICATION AT LOW BIT RATES . . . . . . . . . . 441Dimitris Agrafiotis, Nishan Canagarajah, Dave Bull, Jim Kyle, Helen Seers, University of Bristol, UK; andMatthew Dye, University of Rochester, USA

DCT-BASED PHASE CORRELATION MOTION ESTIMATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445Min Li, Mainak Biswas, Sanjeev Kumar and Truong Nguyen, UCSD, ECE Dept., USA

A NEW RATE CONTROL SCHEME FOR H.264 VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449Peng Yin and Jill Boyce, Corporate Research, Thomson Inc, USA

AN EARLY DETECTION OF ALL-ZERO DCT BLOCKS IN H.264. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453Gyu Yeong Kim, Department of Electronics Engineering, Pusan National University, South Korea; Yong Ho Moon,Division of Digital and Information Engineering, Pusan University of Foreign Studies, South Korea; and Jae HoKim, Department of Electronics Engineering, Pusan National University, South Korea

ENERGY SCALABILITY IN MULTIMEDIA CODEC USING NQDCT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457Ming-Yan Chan and Chi-Wah Kok, Dept. EEE, Hong Kong University of Science and Technology, Hong Kong

A FAST H.264 INTRA PREDICTION ALGORITHM USING MACROBLOCK PROPERTIES . . . . . . . . . . . . . . . . 461Chun-ling Yang, College of Electronic and Information Engineering, South China University of Technology, China;Lai-Man Po and Wing-Hong Lam, Department of Electronic Engineering, City University of Hong Kong, HongKong

INTER FRAME CODING WITH TEMPLATE MATCHING SPATIO-TEMPORAL PREDICTION . . . . . . . . . . . . 465Kazuo Sugimoto, Sadaatsu Kato, Choong Seng Boon, Mitsuru Kobayashi and Yoshinori Suzuki, NTT DoCoMo,Inc., Japan

NEW SCALING TECHNIQUE FOR DIRECT MODE CODING IN B PICTURES . . . . . . . . . . . . . . . . . . . . . . . . . . . 469Xiangyang Ji, Debin Zhao, Wen Gao, Institute of Computing Technology, Chinese Academy of Sciences, Beijing,China; Yan Lu, Harbin Institute of Technology, Harbin, China; and Siwei Ma, Institute of Computing Technology,Chinese Academy of Sciences, Beijing, China

TREE STRUCTURED HYBRID INTRA PREDICTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473Satoshi Kondo, Hisao Sasai and Shinya Kadono, Matsushita Electric Industrial Co., Ltd., Japan

PERCEPTUALLY WEIGHTED DISTORTION MEASURE IN LOW BITRATE BLOCK BASED VIDEOCODERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477Jaehan In, Ali Jerbi, UB Video Inc., Canada; and Foued Ben Amara, University of Toronto, Canada

VARIABLE BLOCK-SIZE TRANSFORM AND ENTROPY CODING AT THE ENHANCEMENT LAYER OFFGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481Jungong Han, ISN national laboratory of Xidian University, China; Xiaoyan Sun, Feng Wu, Shipeng Li, MicrosoftResearch Asia, China; and Zhaoyang Lu, ISN national laboratory of Xidian University, China

HIERARCHICAL MODE SEARCH WITH CLASSIFICATION OF BISECTIONAL PREDICTION MODESBASED ON THE POSITION OF MOTION BOUNDARY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485Sadaatsu Kato, Kazuo Sugimoto, Fulvio Moschetti and Choon Seng Boon, NTT DoCoMo, Inc., Japan

PERCEPTUALLY-ADAPTIVE PRE-PROCESSING FOR MOTION-COMPENSATED RESIDUE IN VIDEOCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489Xiaokang Yang, Weisi Lin, Zhongkang Lu, Ee Ping Ong and Susu Yao, Institute for Infocomm Research, Singapore

SESSION MA-P7: Image Compression and Applications

JPEG-MATCHED DATA FILLING OF SPARSE IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493George Pavlidis, Sofia Tsekeridou and Christodoulos Chamzas, Democritus University of Thrace, Greece

A TWO-DIMENSIONAL LIFTING SCHEME OF INTEGER WAVELET TRANSFORM FOR LOSSLESSIMAGE COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497Yan-Kui Sun, Tsinghua University, China

PALETTE REORDERING UNDER AN EXPONENTIAL POWER DISTRIBUTION MODEL OF PREDICTIONRESIDUALS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501Armando Pinho, DET/IEETA, University of Aveiro, Portugal; and Antonio Neves, IEETA, University of Aveiro,Portugal

A COMPARISON OF NON-ORTHOGONAL AND ORTHOGONAL FRACTAL DECODING . . . . . . . . . . . . . . . . 505Ming Hong Pi, Anup Basu, Dept. of Computing Science, University of Alberta, Canada; Mrinal Mandal, Dept.of Electrical and Computer Engineering, University of Alberta, Canada; and Hua Li, Dept. of Mathematics andComputer Science, University of Lethbridge, Canada

ANALYSIS/SYNTHESIS SYSTEMS FOR PROGRESSIVE-TO-LOSSLESS EMBEDDED WAVELET IMAGECODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509Kunitoshi Komatsu and Kaoru Sezaki, University of Tokyo, Japan

COMPARISON OF LOSSY TO LOSSLESS COMPRESSION TECHNIQUES FOR DIGITAL CINEMA. . . . . . . 513Stefano Andriani, Giancarlo Calvagno, Tomaso Erseghe, Gian Antonio Mian, DEI - University of Padova, Italy;Marco Durigon, Roberto Rinaldo, DIEGM - University of Udine, Italy; Mike Knee, Paul Walland, Snell & WilcoxLtd., UK; and Michael Koppetz, Arnold & Richter Cine Technik (ARRI), Germany

LOSSLESS COMPRESSION OF COLOR MOSAIC IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517Ning Zhang and Xiaolin Wu, McMaster University, Canada

DEMOSAICKING AND JPEG2000 COMPRESSION OF MICROSCOPY IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . 521Benoıt Parrein, Marc Tarin and Patrick Horain, GET/INT, France

QUALITY AND COMPLEXITY COMPARISON OF H.264 INTRA MODE WITH JPEG2000 AND JPEG. . . . . 525Aravind Al, Bindu P. Rao, Sudhir S. Kudva, National Institute of Technology Karnataka, Surathkal, India; SreenuBabu, Texas Instruments (India) Ltd., Bangalore, India; Sumam David S., National Institute of Technology Kar-nataka, Surathkal, India; and Ajit V. Rao, Texas Instruments (India) Ltd., Bangalore, India

SESSION MA-P8: Distributed Source Coding and Others

DISTRIBUTED COMPRESSION OF THE PLENOPTIC FUNCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529Nicolas Gehrig and Pier Luigi Dragotti, Imperial College London, UK

JOINT DATA COMPRESSION AND ERROR PROTECTION FOR COLLABORATIVE TRANSMISSION . . . . 533Haitong Sun, Mihaela Van der Schaar and Zhi Ding, University of California Davis, USA

ERROR RESILIENCE SUPPORTING BI-DIRECTIONAL FRAME RECOVERY FOR VIDEO STREAMING . 537Kai-Chao Yang, Chun-Ming Huang and Jia-Shung Wang, Department of Computer Science, Tsing Hua University,Taiwan

H.264-BASED STREAM MORPHING WITH SCALABLE MOTION CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541James Macnicol, Michael Frater and John Arnold, University College, The University of New South Wales, Aus-tralia

H.264/AVC DATA PARTITIONING FOR MOBILE VIDEO COMMUNICATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . 545Thomas Stockhammer, Munich University of Technology, Germany; and Maja Bystrom, Boston University, USA

SESSION MP-S1: Deformable Models and Applications

APPROXIMATION OF IMAGES BY BASIS FUNCTIONS FOR MULTIPLE REGION SEGMENTATIONWITH LEVEL SETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549Carlos Vazquez, INRS-EMT, Canada; Abdol-Reza Mansouri, DEAS, Harvard University, USA; and Amar Mitiche,INRS-EMT, Canada

JOINT DENSE 3D INTERPRETATION AND MULTIPLE MOTION SEGMENTATION OF TEMPORALIMAGE SEQUENCES: A VARIATIONAL FRAMEWORK WITH ACTIVE CURVE EVOLUTION ANDLEVEL SETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553Hicham Sekkati and Amar Mitiche, INRS-EMT, Canada

ACTIVE CONTOUR MODELS - A MULTISCALE IMPLEMENTATION FOR ANATOMICAL FEATUREDELINEATION IN CERVICAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557Viara Van Raad, The University of New South Wales, Australia

PERSON AUTHENTICATION USING ASM BASED LIP SHAPE AND INTENSITY INFORMATION . . . . . . . 561Lin Leung Mok and Wing Hong Lau, City University of Hong Kong, Hong Kong

SESSION MP-S2: Media Security Issues in Streaming and Mobile Appli-cations

NETWORK FRIENDLY MEDIA SECURITY: RATIONALES, SOLUTIONS, AND OPEN ISSUES . . . . . . . . . . . 565Wenjun Zeng, Xinhua Zhuang and Junqiang Lan, Univ. of Missouri-Columbia, USA

SECURITY EVALUATION FOR COMMUNICATION-FRIENDLY ENCRYPTION OF MULTIMEDIA . . . . . . . 569Yinian Mao and Min Wu, ECE Department, University of Maryland, College Park, USA

A NOVEL LOSSY-TO-LOSSLESS WATERMARKING SCHEME FOR JPEG2000 IMAGES . . . . . . . . . . . . . . . . . 573Zhishou Zhang, Qibin Sun and Wai-Choong Wong, Institute for Infocomm Research, Singapore

SECURE TRANSCODING WITH JPSEC CONFIDENTIALITY AND AUTHENTICATION . . . . . . . . . . . . . . . . . 577Susie Wee and John Apostolopoulos, HP Labs, USA

SESSION MP-L1: Face Detection, Recognition, and Classification I

ESTIMATING THE QUALITY OF FACE LOCALIZATION FOR FACE VERIFICATION . . . . . . . . . . . . . . . . . . . . 581Yann Rodriguez, Fabien Cardinaux, Samy Bengio and Johnny Mariethoz, IDIAP, Switzerland

STATISTICAL TRANSFORMATIONS OF FRONTAL MODELS FOR NON-FRONTAL FACE VERIFICATION 585Conrad Sanderson, University of Adelaide, Australia; and Samy Bengio, IDIAP Research Institute, Switzerland

EFFICIENT FACE ORIENTATION DISCRIMINATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589Shumeet Baluja, Mehran Sahami and Henry Rowley, Google, USA

OMNI-DIRECTIONAL FACE DETECTION BASED ON REAL ADABOOST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593Chang Huang, Bo Wu, Department of Computer Science and Technology, Tsinghua University, China; Haizhou Ai,Department of Computer Science and Technology, Tsinghua University, Beijing 100084, P.R.China, China; andShihong Lao, Sensing Technology Laboratory, Omron Corporation, Japan

A ROBUST FACE DETECTOR UNDER PARTIAL OCCLUSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 597Kazuhiro Hotta, The University of Electro-Communications, Japan

MEAN-SHIFT BASED MIXTURE MODEL FOR FACE DETECTION IN COLOR IMAGE . . . . . . . . . . . . . . . . . . 601Tze-Yin Chow and Kin-Man Lam, The Hong Kong Polytechnic University, Hong Kong

STEREO HEAD/FACE DETECTION AND TRACKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 605Jian Gang Wang, Ronda Venkateswarlu and Eng Thiam Lim, Institute for Infocomm Research, Singapore

MARGIN-MAXIMIZATION DISCRIMINANT ANALYSIS FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . 609Yan Zhu and Eric Sung, Nanyang Technological University, Singapore

SESSION MP-L2: Video Summarization and Browsing

A RATE-CONSTRAINED KEY-FRAME EXTRACTION SCHEME FOR CHANNEL-AWARE VIDEOSTREAMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613Yu-Hsuan Ho, National Chung Cheng University, Taiwan; Wei-Ren Chen, Ulead, Taiwan; and Chia-Wen Lin,National Chung Cheng University, Taiwan

OPTIMAL VIDEO SUMMARIZATION WITH A BIT BUDGET CONSTRAINT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617Zhu Li, Motorola Labs, Schaumburg, USA; Guido Schuster, Hochschule for Technik Rapperswil, Switzerland;Aggelos Katsaggelos, Northwestern University, Evanston, USA; and Bhavan Gandhi, Motorola Labs, Schaumburg,USA

AN IMPORTANCE MEASUREMENT FOR VIDEO AND ITS APPLICATION TO TV NEWS ITEMSDISTILLATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621Jin-Hau Kuo, Chin-Wei Fang, Jen-Hao Yeh and Ja-Ling Wu, Communication and Multimedia Laboratory, Depart-ment of Computer Science and Information Engineering, National Taiwan University, Taiwan

A NEW APPROCH TO AUTOMATIC MUSIC VIDEO SUMMARIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625Xi Shao, Changsheng Xu, Institute for Infocomm Research, Singapore; and Mohan Kankanhalli, National Univer-asity of Singapore, Singapore

A GENERIC MID-LEVEL REPRESENTATION FOR SEMANTIC VIDEO ANALYSIS . . . . . . . . . . . . . . . . . . . . . . 629Qing Tang, School of Information Technologies, University of Sydney, Australia; Joo-Hwee Lim, Institute forInfocomm Research, Singapore; Jesse S. Jin, School of Information Technologies, University of Sydney, Australia;Haiping Sun, Institute for Infocomm Research, National University of Singapore, Singapore; and Qi Tian, Institutefor Infocomm Research, Singapore

DYNAMIC BAYESIAN NETWORK BASED EVENT DETECTION FOR SOCCER HIGHLIGHTEXTRACTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633Fei Wang, Institute of Computing Technology, Chinese Academy of Sciences, China; Yu-Fei Ma, Hong-JiangZhang, Microsoft Research Asia, China; and Jin-Tao Li, Institute of Computing Technology, Chinese Academyof Sciences, China

GROUPING VIDEO SHOTS INTO SCENES BASED ON 1D MOSAIC DESCRIPTORS . . . . . . . . . . . . . . . . . . . . . 637Henri Nicolas, Anne Manoury, INRIA, France; Jenny Benois-Pineau, Labri, University of Bordeaux, France;William Dupuis and Dominique Barba, IRCCyn, France

DISTRIBUTED MPEG-7 IMAGE INDEXING USING SMALL WORLD USER AGENTS . . . . . . . . . . . . . . . . . . . 641Panagiotis Androutsos, Azadeh Kushki, University of Toronto, Canada; Dimitrios Androutsos, Ryerson PolytechnicUniversity, Canada; Kostantinos Plataniotis and Anastasios Venetsanopoulos, University of Toronto, Canada

SESSION MP-L3: Image Filtering and Partial Differential Equations

AUTOMATIC IMAGE DECOMPOSITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 645Kedar Patwardhan and Guillermo Sapiro, Dept. of Electrical Engineering and Digital Technology Center, Univer-sity of Minnesota, Minneapolis, USA

A PARTIAL DIFFERENTIAL EQUATION APPROACH TO IMAGE ZOOM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 649Abdelmounim Belahmidi, Ceremade, France; and Frederic Guichard, Do Labs, France

A NEW APPROACH TO THINNING BASED ON TIME-REVERSED HEAT CONDUCTION MODEL . . . . . . . 653Xinhua Ji and Jufu Feng, School of Electronics Engineering and Computer Science, Peking University, China

MULTIPLICATIVE MULTIRESOLUTION DECOMPOSITION FOR 2-D SIGNALS: APPLICATION TOSPECKLE REDUCTION IN SAR IMAGES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657Serir Amina, U.S.T.H.B, Algeria; and Belouchrani Adel, E.N.P, Algeria

ISOTROPIC-POLYHARMONIC B-SPLINES AND WAVELETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661Dimitri Van De Ville, Thierry Blu, Brigitte Forster and Michael Unser, Swiss Federal Institute of TechnologyLausanne, Switzerland

AN IMPLEMENTED ARCHITECTURE OF DEBLOCKING FILTER FOR H.264/AVC . . . . . . . . . . . . . . . . . . . . . . 665Bin Sheng, Department of Computer Science and Technology, Harbin Institute of Technology, China, China; WenGao, Institute of Computing Technology, Chinese Academy of Sciences, China, China; and Di Wu, Department ofComputer Science and Technology, Harbin Institute of Technology, China, China

A NEW SIMILARITY MEASURE USING HAUSDORFF DISTANCE MAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669Etienne Baudrier, Gilles Millon, Frederic Nicolier and Su Ruan, CReSTIC, France

CONTOUR SIMPLIFICATION USING NON-LINEAR DIFFUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673Antonio Pinheiro, Universidade da Beira Interior, Portugal; and Mohammed Ghanbari, University of Essex, UK

SESSION MP-L4: Image/Video Indexing and Retrieval

ROBUST PERCEPTUAL IMAGE HASHING USING FEATURE POINTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 677Vishal Monga and Brian L. Evans, University of Texas, Austin, USA

FEATURE STATISTICAL RETRIEVAL APPLIED TO CONTENT-BASED COPY IDENTIFICATION . . . . . . . . 681Alexis Joly, Olivier Buisson, Institut National de l’Audiovisuel (INA), France; and Carl Frelicot, Universite de LaRochelle, France

ROBUST VIDEO SIGNATURE BASED ON ORDINAL MEASURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685Xian-Sheng Hua, Microsoft Research Asia, China; Xian Chen, Tsinghua University, China; and Hong-JiangZhang, Microsoft Research Asia, China

IMAGE RETRIEVAL BASED ON FEATURE WEIGHTING AND RELEVANCE FEEDBACK . . . . . . . . . . . . . . . 689Mohammed Lamine Kherfi and Djemel Ziou, Departement d’informatique, Universite de Sherbrooke, Canada

SEMANTIC-BASED TRAFFIC VIDEO RETRIEVAL USING ACTIVITY PATTERN ANALYSIS . . . . . . . . . . . . 693Dan Xie, Weiming Hu, Tieniu Tan, National Laboratory of Pattern Recognition, China; and Junyi Peng, BeijingUniversity of Aeronautics and Astronautics, China

DETECTION OF UNIQUE PEOPLE IN NEWS PROGRAMS USING MULTIMODAL SHOT CLUSTERING . 697Cuneyt Taskiran, Purdue University, USA; Alberto Albiol, Technical University of Valencia, Spain; Luis Torres,Technical University of Catalonia, Spain; and Edward Delp, Purdue University, USA

A SIMPLE AND FAST COLOR-BASED HUMAN FACE DETECTION SCHEME FOR CONTENT-BASEDINDEXING AND RETRIEVAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 701Sangkeun Lee and Monson H. Hayes, Georgia Institute of Technology, USA

A PINHOLE CAMERA MODELING OF MOTION VECTOR FIELD FOR TENNIS VIDEO ANALYSIS. . . . . . 705Peng Wang, Rui Cai, Bin Li and Shi-Qiang Yang, Dept. Computer Science, Tsinghua Univ., Beijing, China

SESSION MP-L5: Watermarking II

BLIND SOURCE CAMERA IDENTIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 709Mehdi Kharrazi, Husrev T. Sencar and Nasir Memon, Polytechnic University, USA

BI-LEVEL IMAGE WATERMARKING FOR IMAGE AUTHENTICATION SURVIVING JPEG LOSSYCOMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713Jagdish C. Patra, Chong How Tan and Ee-Luang Ang, Nanyang Technological University, Singapore

QIM WATERMARKING GAMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717Anil Kumar Goteti and Pierre Moulin, University of Illinois, Urbana-Champaign, USA

IMPROVE SECURITY OF FRAGILE WATERMARKING VIA PARAMETERIZED WAVELET . . . . . . . . . . . . . . 721Jiwu Huang, Junquan Hu, Daren Huang, Sun Yat-Sen University, China; and Yun Q. Shi, New Jersey Institute ofTechnology, USA

A ROBUST SPREAD-SPECTRUM WATERMARKING METHOD USING TWO-LEVEL QUANTIZATION . . 725Anthony T.S. Ho and Feng Shu, Nanyang Technological University, Singapore

WATERMARKING 3D SHAPES USING LOCAL MOMENTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 729Adrian Bors, University of York, UK

AN ATTACK TO BPCS-STEGANOGRAPHY USING COMPLEXITY HISTOGRAM ANDCOUNTERMEASURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733Michiharu Niimi, Tomohito Ei, Hideki Noda, Eiji Kawaguchi, Kyushu Institute of Technology, Japan; and BruceSegee, University of Maine, USA

A RST RESILIENT OBJECT-BASED VIDEO WATERMARKING SCHEME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737Dajun He and Qibin Sun, Institute for Infocomm Research (I2R), Singapore

SESSION MP-P1: Video Compression Standards II

FAST MACROBLOCK MODE SELECTION BASED ON MOTION CONTENT CLASSIFICATION INH.264/AVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 741Ming Yang and Wensheng Wang, Dept. of Electronic Engineering, Tsinghua Univ., China

ADAPTIVE RATE CONTROL FOR H.264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745Zhengguo Li, Feng Pan, Keng Pang Lim, Xiao Lin and Susanto Rahardja, Institute for Infocomm Research, Singa-pore

TIME-EFFICIENT LEARNING THEORETIC ALGORITHMS FOR H.264 MODE SELECTION . . . . . . . . . . . . . 749Ashish Jagmohan, University of Illinois, Urbana-Champaign, USA; and Krishna Ratakonda, IBM T.J. WatsonResearch Centre, USA

RATE-DISTORTION OPTIMIZED VIDEO CODING WITH STOPPING RULES: QUALITY ANDCOMPLEXITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 753Marcos Moecke and Rui Seara, Federal University of Santa Catarina, Brazil

REAL-TIME H.264/AVC CODEC ON INTEL ARCHITECTURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 757Vaughn Iverson, Jeff McVeigh and Bob Reese, Intel Corporation, USA

OPTIMAL BIT ALLOCATION FOR MPEG-4 MULTIPLE VIDEO OBJECTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 761Zhenzhong Chen and King Ngi Ngan, Department of Electronic Engineering, The Chinese University of HongKong, Hong Kong

LOW-COMPLEXITY MACROBLOCK MODE SELECTION FOR H.264/AVC ENCODERS . . . . . . . . . . . . . . . . . 765Hyungjoon Kim and Yucel Altunbasak, Georgia Institute of Technology, USA

FEATURE-BASED INTRA-PREDICTION MODE DECISION FOR H.264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 769Changsung Kim, University of Southern California, USA; Hsuan-Huei Shih, Ali Microelectronics Corp., USA; andC. -C. Jay Kuo, University of Southern California, USA

COEFFICIENT THRESHOLDING AND OPTIMIZED SELECTION OF THE LAGRANGIAN MULTIPLIERFOR NON-REFERENCE FRAMES IN H.264 VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 773Pontus Carlsson, Linkopings Universitet, Sweden; F. Pan, Institute for Infocomm Research, Singapore; and Liang-Tien Chia, Nanyang Technological University, Singapore

EFFICIENT MEMORY MANAGEMENT CONTROL FOR H.264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 777Hyukjune Chung and Antonio Ortega, University of Southern California, USA

FAST INTRA MODE DECISION ALGORITHM FOR H.264/AVC VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . 781F. Pan, X. Lin, S. Rahardja, K. Lim, Z. Li, Institute for Infocomm Research, Singapore; C. Zhu, NTU, Singapore;D. Wu, S. Wu, Institute for Infocomm Research, Singapore; W. Ye and Z. Liang, NTU, Singapore

INTER-PLANE PREDICTION FOR RGB VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 785Woo-Shik Kim, Dae-Sung Cho and Hyun Mun Kim, Samsung Advanced Institute of technology, South Korea

FAST MACROBLOCK INTER MODE DECISION AND MOTION ESTIMATION FOR H.264/MPEG-4 AVC . 789Zhi Zhou and Ming-Ting Sun, Department of Electrical Engineering, University of Washington, USA

A STUDY ON FAST RATE-DISTORTION OPTIMIZED CODING MODE DECISION FOR H.264 . . . . . . . . . . . 793Akiyuki Tanizawa, Shinichiro Koto, Takeshi Chujoh, Toshiba Corporation, Corporate Research & DevelopmentCenter, Multimedia Laboratory, Japan; and Yoshihiro Kikuchi, TOSHIBA Corporation, Core Technology Center,Japan

SESSION MP-P2: Error Resilience/Concealment II

MOTION-BASED SHAPE ERROR CONCEALMENT FOR OBJECT-BASED VIDEO . . . . . . . . . . . . . . . . . . . . . . . 797Luis Soares and Fernando Pereira, Instituto Superior Tecnico / Instituto de Telecomunicacoes, Portugal

RATE DISTORTION ANALYSIS OF LEAKY PREDICTION LAYERED VIDEO CODING USINGQUANTIZATION NOISE MODELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 801Yuxin Liu, Purdue University, USA; Josep Prades-Nebot, Universidad Politecnica de Valencia, Spain; Paul Salama,Indiana University-Purdue University Indianapolis, USA; and Edward Delp, Purdue University, USA

MARKOV RANDOM FIELD ESTIMATION OF LOST DCT COEFFICIENTS IN JPEG DUE TO PACKETERRORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 805Jinwha Yang and Edward Delp, Purdue University, USA

EDGE DIRECTED FILTER BASED ERROR CONCEALMENT FOR WAVELET-BASED IMAGES . . . . . . . . . . 809Shuiming Ye, Qibin Sun, Institute for Infocomm Research, Singapore; and Ee-Chien Chang, National Universityof Singapore, Singapore

MINIMIZING A WEIGHTED ERROR CRITERION FOR SPATIAL ERROR CONCEALMENT OF MISSINGIMAGE DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 813Katrin Meisinger and Andre Kaup, University of Erlangen-Nuremberg, Germany

DESING OF REVERSIBLE VARIABLE-LENGTH CODES USING PROPERTIES OF THE HUFFMAN CODEAND AVERAGE LENGTH FUNCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 817Wook-Hyun Jeong, Samsung Electronics Co., Korea; Young-Suk Yoon and Yo-Sung Ho, GIST, Korea

ERROR RESILIENCE ANALYSIS OF MULTI-HYPOTHESIS MOTION COMPENSATED PREDICTION FORVIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 821Wei-Ying Kung, University of Southern California, USA; Chang-Su Kim, the Chinese University of Hong Kong,Hong Kong; and C.-C. Jay Kuo, University of Southern California, USA

AN INTRA-FRAME ERROR CONCEALMENT: NON-LINEAR PATTERN ALIGNMENT ANDDIRECTIONAL INTERPOLATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 825Wuttipong Kumwilaisak, King Mongkut University of Technology, Thailand; and Frank Hartung, Ericsson Re-search Lab, Germany

EFFICIENT ERROR RECOVERY FOR MULTIPLE DESCRIPTION VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . 829Guanjun Zhang and Robert Stevenson, University of Notre Dame, USA

EFFICIENT PACKET LOSS PROTECTION FOR JPEG2000 IMAGES ENABLING BACKWARDCOMPATIBILITY WITH A STANDARD DECODER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833Khairul Munadi, Masayuki Kurosaki, Kiyoshi Nishikawa and Hitoshi Kiya, Tokyo Metropolitan University, Japan

ERROR-RESILIENT WIRELESS VIDEO TRANSMISSION USING MOTION-BASED UNEQUAL ERRORPROTECTION AND INTRA-FRAME PACKET INTERLEAVING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837Qi Qu, Electrical and Computer Engineering Dept., Univ. of California San Diego, USA; Yong Pei, ComputerScience and Engineering Dept., Wright State Univ., USA; James W. Modestino and Xusheng Tian, Electrical andComputer Engineering Dept., Univ. of Miami, USA

ON PACKETIZATION OF JPEG2000 CODE-STREAMS IN WIRELESS CHANNELS. . . . . . . . . . . . . . . . . . . . . . . 841Hua Cai, Microsoft Research Asia, China; and Bing Zeng, The Hong Kong University of Science and Technology,Hong Kong

CONTENT-BASED PERIODIC MACROBLOCK FOR ERROR-RESILIENT TRANSMISSION OF H.264VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 845Jinghong Zheng and Lap-Pui Chau, Nanyang Technological University, Singapore

SESSION MP-P3: Biometrics I

CLASSIFICATION OF FINGERPRINTS USING SINGULAR POINTS AND THEIR PRINCIPAL AXES . . . . . 849Chainarong Klimanee and Dinh Thong Nguyen, University of Tasmania, Australia

A SVM-BASED METHOD FOR FACE RECOGNITION USING A WAVELET-PCA REPRESENTATION OFFACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 853Majid Safari, Mehrtash Tafazzoli Harandi and Babak Araabi, Department of Electrical and Computer Engineer-ing, University of Tehran, Iran

AN ANGULAR TRANSFORM OF GAIT SEQUENCES FOR GAIT ASSISTED RECOGNITION . . . . . . . . . . . . 857Nikolaos Boulgouris, Konstantinos Plataniotis and Dimitris Hatzinakos, University of Toronto, Canada

IRIS FEATURES EXTRACTION USING WAVELET PACKETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 861Erik Rydgren, Thomas Ea, Frederic Amiel, Florence Rossant and Amara Amara, Institut Superieur d’Electroniquede Paris, ISEP, France

DISCRIMINANT IRIS FEATURE AND SUPPORT VECTOR MACHINES FOR IRIS RECOGNITION . . . . . . . 865Byungjun Son, Hyunsuk Won, Gyundo Kee and Yillbyung Lee, Division of Computer and Information Engineering,Yonsei University, South Korea

NOISE REMOVAL AND IMPAINTING MODEL FOR IRIS IMAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 869Junzhou Huang, Yunhong Wang, Jiali Cui and Tieniu Tan, National Laboratory of Pattern Recognition, Institute ofAutomation,CAS, China

ONE-TIME CALIBRATION EYE GAZE DETECTION SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873Choon Kiat Lim and Surendra Ranganath, National University of Singapore, Singapore

POSTURE RECOGNITION OF NUCLEAR POWER PLANT OPERATORS BY SUPERVISED LEARNING . . 877Chikahito Nakajima, Central Research Institute of Electric Power Industry, Japan

ACTION MODELING WITH VOLUMETRIC DATA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 881Fabio Cuzzolin, Augusto Sarti and Stefano Tubaro, DEI - Politecnico di Milano, Italy

MODEL BASED ALGORITHM FOR SINGULAR POINT DETECTION FROM FINGERPRINT IMAGES. . . . 885Nannan Wu and Jie Zhou, Department of Automation,Tsinghua University, China

ON-LINE WRITER RECOGNITION FOR THAI BASED ON VELOCITY OF BARYCENTER OF PEN-POINTMOVEMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 889Pitak Thumwarin and Takenobu Matsuura, Tokai University, Japan

M-BAND WAVELETS APPLICATION TO TEXTURE ANALYSIS FOR PALMPRINT RECOGNITION . . . . . . 893Dai Qingyun, Bi Ning, Huang Daren, Zhongshan University, China; David Zhang, Hongkong Polyu, Hong Kong;and Li Feng, Zhongshan University, China

REDUCED-COMPLEXITY BIOMETRIC RECOGNITION USING 1-D CROSS-SECTIONS OFCORRELATION FILTERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 897Jason Thornton and Vijayakumar Bhagavatula, Carnegie Mellon University, USA

SESSION MP-P4: Image Segmentation: By Multiple Features and OtherMethods

ADAPTIVE SKIN DETECTION USING MULTIPLE CUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 901Jinfeng Yang, Zhouyu Fu, Tieniu Tan and Weiming Hu, Institute of Automation, Chinese Academy of Science,National Laboratory of Pattern Recognition, China

EFFICIENT FUZZY-CONNECTEDNESS SEGMENTATION USING SYMMETRIC CONVOLUTION ANDADAPTIVE THRESHOLDING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905Shu-Yen Wan, Jung-Tai Chen and Shu-Hung Yeh, Chang Gung University, Taiwan

IMAGE SEGMENTATION VIA BRITTLE FRACTURE MECHANICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 909Wei Wang and Ronald Chung, Dept. of ACAE, Chinese Univ. of HongKong, China

DIMENSIONALITY REDUCTION IN HYPERSPECTRAL IMAGE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . 913Huiwen Zeng and H. Joel Trussell, ECE Dept, NC State Univ, USA

AUTOMATIC SEGMENTATION OF BRAIN MRI THROUGH LEARNING BY EXAMPLE . . . . . . . . . . . . . . . . . 917Horacio Legal-Ayala and Jacques Facon, Pontificia Universidade Catolica do Parana - PPGIA, Brazil

PERCEPTUALLY-TUNED MULTISCALE COLOR-TEXTURE SEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . 921Junqing Chen, Thrasyvoulos N. Pappas, Northwestern University, USA; Aleksandra Mojsilovic and Bernice E.Rogowitz, IBM T.J. Watson Research Center, USA

MULTI-SCALE SPACE VEHICLE COMPONENT IDENTIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 925William Wai Leung Lam, Clement Chun Cheong Pang and Nelson Hon Ching Yung, The University of Hong Kong,Hong Kong

OBJECT RECOGNITION BASED ON BINARY PARTITION TREES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 929Oreste Salerno, Montse Pardas, Veronica Vilaplana and Ferran Marques, Universitat Politecnica de Catalunya,Spain

EFFICIENT PROPOSAL DISTRIBUTIONS FOR MCMC IMAGE SEGMENTATION . . . . . . . . . . . . . . . . . . . . . . . 933Timo Kostiainen, Helsinki University of Technology, Laboratory of Computational Engineering, Finland; andJouko Lampinen, Helsinki University of Technology,Laboratory of Computational Engineering, Finland

CONTOUR TRACKING BY MINIMAL COST PATH APPROACH. APPLICATION TO CEPHALOMETRY. . . 937Barbara Romaniuk, GREYC CNRS UMR 6072, France; Michel Desvignes, LIS, France; Marinette Revenu, GR-EYC CNRS UMR 6072, France; and Marie-Josephe Deshayes, TeleCrane Innovation, France

TOWARDS UNSUPERVISED ATTENTION OBJECT EXTRACTION BY INTEGRATING VISUALATTENTION AND OBJECT GROWING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 941Junwei Han, School of Computer Engineering, Nangyang Technological University, Singapore; King N. Ngan,Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong; Mingjing Li andHongjiang Zhang, Microsoft Research Asia, China

IMAGE SEGMENTATION BY COOPERATIVE OPTIMIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 945Xiaofei Huang, CallVista, Inc., USA

A CONNECTIVITY SOLUTION FOR EXTRACTION OF THIN OBJECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 949Marco Antonelli, Silvana Dellepiane, Gianni Vernazza and Lorena Novelli, Univ. of Genoa - Dept. of Biophysicaland Electronic Engineering, Italy

3D-COLOR-STRUCTURE-CODE - SEGMENTATION BY USING A NEW NON-PLAINNESS ISLANDHIERARCHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 953Patrick Sturm, University of Koblenz, Germany

SESSION MP-P5: Image Enhancement II

ADAPTIVE WAVELET RESTORATION OF NOISY VIDEO SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 957Nasir Rajpoot, Zhen Yao and Roland Wilson, University of Warwick, UK

DIGITAL IMAGE INPAINTING USING MONTE CARLO METHOD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 961Jianping Gu, Silong Peng and Xuelin Wang, Institute of Automation, Chinese Academy of science, China

ADAPTIVE SPATIO-TEMPORAL FILTERING FOR VIDEO DE-NOISING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 965Hye-Yeon Cheong, Columbia University, USA; Alexis Michael Tourapis, Joan Llach and Jill Boyce, ThomsonCorporate Research, USA

THEORETICAL ANALYSIS OF SOME REGULARIZED IMAGE DENOISING METHODS. . . . . . . . . . . . . . . . . 969Patrick L. Combettes and Valerie R. Wajs, Universite Paris 6, France

IMAGE FUSION BASED ON NON-NEGATIVE MATRIX FACTORIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 973Junying Zhang, Electronics Engineering Institute, Xidian University, China; Le Wei, School of Computer Sci-ence, Xidian University, China; Qiguang Miao, Guilin Institute of Electronic Technology, China; and Yue Wang,Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, USA

IMAGE DENOISING USING FREBAS MULTI-RESOLUTION IMAGE ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . 977Satoshi Ito, Graduate School of Eng. Utsunomiya Univ., Japan; and Yoshifumi Yamada, Faculty of Eng. Ut-sunomiya Univ, Japan

CONCEALMENT OF INTERPOLATION ERRORS FOR LOW BIT-RATE MOTION-COMPENSATEDINTERPOLATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 981Yan Wu, M.N.S. Swamy and M. Omair Ahmad, Concordia University, Canada

LEAST-SQUARES INTERBAND DENOISING OF COLOR AND MULTISPECTRAL IMAGES . . . . . . . . . . . . . 985Paul Scheunders and Jef Driesen, University of Antwerp, Belgium

CONTRAST ENHANCEMENT OF RADIOGRAPH IMAGES BASED ON LOCAL HETEROGENEITYMEASURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 989Idris El-Feghi, Maher Sid-Ahmed, Mijid Ahmadi and Songtao Huang, University of Windsor, Canada

VISUAL CONTENT ADAPTATION FOR LOW VISION USERS IN MPEG-21 FRAMEWORK . . . . . . . . . . . . . . 993Truong Cong Thang and Yong Man Ro, Information and Communication University, South Korea

UNIVERSAL MINIMAX BINARY IMAGE DENOISING UNDER CHANNEL UNCERTAINTY . . . . . . . . . . . . . 997George Gemelos, Styrmir Sigurjonsson and Tsachy Weissman, Stanford University, USA

A FAST AND ADAPTIVE METHOD FOR IMAGE CONTRAST ENHANCEMENT . . . . . . . . . . . . . . . . . . . . . . . . 1001Zeyun Yu and Chandrajit Bajaj, Department of Computer Science, University of Texas at Austin, USA

SHIFT-INVARIANT WAVELET DENOISING USING INTERSCALE DEPENDENCY . . . . . . . . . . . . . . . . . . . . . . 1005Pei Chen and David Suter, Dept ECSE, Monash University, Australia

SESSION MP-P6: Video Object Tracking

MULTIPLE VIEW TRACKING OF HUMAN MOTION MODELLED BY KINEMATIC CHAINS . . . . . . . . . . . . 1009Aravind Sundaresan, University of Maryland, College Park, USA; Amit RoyChowdhury, University of California,Riverside, USA; and Rama Chellappa, University of Maryland, College Park, USA

MULTI-RESOLUTION PARAMETRIC REGION TRACKING FOR 2D OBJECT REPLACEMENT IN VIDEO 1013Paul Brasnett, David Bull and Nishan Canagarajah, University of Bristol, UK

ROBUST SHAPE BASED TWO HAND TRACKER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1017Ketan Barhate, Kritikal Solutions Pvt. Ltd., India; Kaustubh Patwardhan, Sumantra Dutta Roy, Subhasis Chaud-huri, Indian Institute of Technology, Bombay, India; and Santanu Chaudhury, Indian Institute of Technology, Delhi,India

FACE CONTOUR TRACKING IN VIDEO USING ACTIVE CONTOUR MODEL. . . . . . . . . . . . . . . . . . . . . . . . . . . 1021Xiong Bing, Yu Wei and Charoensak Charayaphan, EEE,NTU, Singapore

AIR-BORNE APPROACHING TARGET DETECTION AND TRACKING IN INFRARED IMAGE SEQUENCE 1025Mukesh Zaveri, Shabbir Merchant and Uday Desai, Indian Institute of Technology-Bombay, India

A FAST AND ROBUST SIMULTANEOUS POSE TRACKING AND STRUCTURE RECOVERY ALGORITHMFOR AUGMENTED REALITY APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1029Ying-Kin Yu, Kin-Hong Wong, Department of Computer Science and Engineering, The Chinese University of HongKong, Hong Kong; and Michael Ming-Yuen Chang, Department of Information Engineering, The Chinese Univer-sity of Hong Kong, Hong Kong

A MULTICAMERA FUSION FRAMEWORK FOR MULTIPLE OCCLUDING OBJECTS TRACKING ININTELLIGENT MONITORING AND SPORT VIEWING APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1033Luca Marchesotti, Gianni Vernazza and Carlo Regazzoni, DIBE - University of Genoa, Italy

BAYESIAN INTEGRATION OF A DISCRETE CHOICE PEDESTRIAN BEHAVIORAL MODEL AND IMAGECORRELATION TECHNIQUES FOR AUTOMATIC MULTI OBJECT TRACKING . . . . . . . . . . . . . . . . . . . . . . . . . 1037Santiago Venegas - Martinez, Gianluca Antonini, Jean-Philippe Thiran, Signal Processing Institute LTS-EPFL,Switzerland; and Michel Bierlaire, Operation Research EPFL, Switzerland

ON-LINE PREDICTIVE APPEARANCE BASED TRACKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1041Namita Gupta, Pooja Mittal, Indian Institute of Technology, Delhi, India; Kaustubh Patwardhan, Sumantra DuttaRoy, Indian Institute of Technology, Bombay, India; Santanu Chaudhury and Subhasis Banerjee, Indian Instituteof Technology, Delhi, India

A PROBABILISTIC COOPERATION BETWEEN TRACKERS OF COUPLED OBJECTS . . . . . . . . . . . . . . . . . . . 1045Ido Leichter, Michael Lindenbaum and Ehud Rivlin, Technion - Israel Institute of Technology, Israel

A TRAJECTORY-BASED BALL DETECTION AND TRACKING ALGORITHM IN BROADCAST TENNISVIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1049Xinguo Yu, Institute for Infocomm Research, Singapore; Chern-Horng Sim, National University of Singapore,Singapore; Jenny Ran Wang, School of Computer Science and Engineering, The University of New South Wales,Sydney 2052, Australia; and Loong Fah Cheong, National University of Singapore, Singapore

SIMULTANEOUS BACKGROUND AND FOREGROUND MODELING FOR TRACKING INSURVEILLANCE VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1053Jie Shao, Shaohua Zhou and Rama Chellappa, University of Maryland, College Park, USA

MULTI-CAMERA CORRESPONDENCE BASED ON PRINCIPAL AXIS OF HUMAN BODY . . . . . . . . . . . . . . . 1057Min Hu, Insititute of Automation, Chinese Academy of Sciences, China; Jianguang Lou, Microsoft Research Asia,China; Weiming Hu and Tieniu Tan, Insititute of Automation, Chinese Academy of Sciences, China

SESSION MP-P7: Biomedical Image Processing: Compression and Regis-tration

APPLYING BINARY PARTITIONING TO WEIGHTED FINITE AUTOMATA FOR IMAGE COMPRESSION 1061Kai Yang and Ghim Hwee Ong, School of Computing, National University of Singapore, Singapore

PROCESSING OF WAVELET TRANSFORM DATA FOR IMPROVED IMAGE COMPRESSION . . . . . . . . . . . . 1065Tanzeem Muzaffar and Tae-Sun Choi, K-JIST, Korea

A NOVEL BOUNDARY HANDLING SCHEME FOR ARBITRARY OBJECT SHAPE IN VIDEO AND IMAGECOMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1069Ka Shun Carson Pun and Truong Q. Nguyen, Department of Electrical and Computering Engineering, Universityof California, San Diego, USA

LEAST-SQUARES MESH MODEL FOR IMAGE COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1073Iciar Alvarez-Cascos, Escuela Tecnica Superior de Ingenieros de Telecomunicacion, Spain; and Yongyi Yang,Illinois Institute of technology, USA

RECONSTRUCTION OF 3D TOOTH IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1077Stephanie Buchaillard, Sim-Heng Ong, National University of Singapore, Singapore; Yohan Payan, UniversiteJoseph Fourier, France; and Kelvin Foong, National University of Singapore, Singapore

SOFT SHAPE CONTEXT FOR ITERATIVE CLOSEST POINT REGISTRATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 1081David Liu and Tsuhan Chen, Carnegie Mellon University, USA

SHEAR-RESIZE FACTORIZATIONS FOR FAST MULTI-MODAL VOLUME REGISTRATION . . . . . . . . . . . . . 1085Ying Chen, Pengwei Hao, Queen Mary, University of London, UK; and Jian Yu, Beijing Jiaotong University, China

TECHNIQUES FOR TEMPORAL REGISTRATION OF RETINAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1089Bin Fang, Department of Computer Science, HKBU, Hong Kong; Wynne Hsu and Mongli Lee, Department ofComputer Science, NUS, Singapore

SESSION MP-P8: Video Coding

RATE-DISTORTION MODELING OF SCALABLE VIDEO CODERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1093Min Dai, Dmitri Loguinov, Texas A & M University, USA; and Hayder Radha, Michigan State University, USA

ON DECODER-LATENCY VERSUS PERFORMANCE TRADEOFFS IN DIFFERENTIAL PREDICTIVECODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1097Prakash Ishwar and Kannan Ramchandran, University of California, Berkeley, USA

LOWPASS FILTERING OF RATE-DISTORTION FUNCTIONS FOR QUALITY SMOOTHING IN REAL-TIME VIDEO RECORDING AND STREAMING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1101Zhihai He, University of Missouri, Columbia, USA; Changwen Chen, Florida Inst. of Tech, USA; and Jianfei Cai,Nanyang Technological Un, Singapore

OBJECT-BASED VIDEO CODING USING A DYNAMIC CODING APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . 1105Marc Chaumont, IRISA/INRIA, France; Stephane Pateux, France Telecom, France; and Henri Nicolas,IRISA/INRIA, France

MODEL-BASED MPEG COMPRESSION OF SYNTHETIC VIDEO SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . 1109Davide Quaglia and Angelo Gattuso, Politecnico di Torino, Italy

DIRECT N-POINT DCT COMPUTATION FROM THREE ADJACENT N/3-POINT DCT COEFFICIENTS. . . . 1113Soo-Chang Pei and Meng-Ping Kao, National Taiwan University, Taiwan

REGION-BASED CODING OF MOTION FIELDS FOR LOW-BITRATE VIDEO COMPRESSION . . . . . . . . . . . 1117Huipin Zhang and Frank Bossen, DoCoMo Communication Labs USA Inc., USA

PROGRESSIVE POLYGON ENCODING OF SEGMENTATION MAPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1121Marc Servais, Theo Vlachos, University of Surrey, UK; and Thomas Davies, BBC, UK

A JOINT DESIGN OF DICTIONARY APPROXIMATION AND MAXIMUM ATOM EXTRACTION FORFAST MATCHING PURSUIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1125Jian-Liang Lin, Wen-Liang Hwang, Institute of Information Science, Academia Sinica, Taiwan, R.O.C., Taiwan;and Soo-Chang Pei, Department of Electrical Engineering, National Taiwan University, Taiwan, R.O.C., Taiwan

IMPROVED DICTIONARIES FOR GENERALIZED BITPLANES-BASED MATCHING PURSUITS VIDEOCODING USING RIDGELETS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1129Leonardo Fonteles, Programa de Engenharia Eletrica/COPPE - Universidade Federal do Rio de Janeiro, Brazil;Rogerio Caetano, Fundacao Desembargador Paulo Feitoza, Brazil; and Eduardo Da Silva, Programa de Engen-haria Eletrica/COPPE - Universidade Federal do Rio de Janeiro, Brazil

CONSTANT QUALITY RATE-CONTROL FOR VIDEO ENCODING BASED ON ACTIVITYSEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1133Luk Overmeire, Vlaamse Radio en Televisie (VRT), Belgium; Fabio Verdicchio, Joeri Barbarien, Peter Schelkens,Vrije Universiteit Brussel, Belgium; and Lode Nachtergaele, Interuniversity MicroElectronics Center, Belgium

RATE-DISTORTION OPTIMAL JOINT MACROBLOCK MODE SELECTION AND MOTION ESTIMATIONFOR MPEG-LIKE VIDEO CODERS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137Hyungjoon Kim and Yucel Altunbasak, Georgia Institute of Technology, USA

EFFICIENT CODING MODE DECISION IN MPEG-4 PART-10 AVC/H.264 MAIN PROFILE. . . . . . . . . . . . . . . . 1141Inchoon Choi, Jeyun Lee and Byeungwoo Jeon, Sungkyunkwan University, Korea

SUBJECTIVE ASSESSMENT OF H.264/AVC VIDEO FOR LOW-BITRATE MULTIMEDIA MESSAGINGSERVICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1145Patrick Brun, Gert Hauske and Thomas Stockhammer, Munich University of Technology, Germany

Table of Contents

Volume II

Tuesday, October26th, 2004

SESSION TA-S1: Content-based Analysis of Multi-modal High Dimen-sional Medical Images

A 3D MODEL OF THE HUMAN LUNG WITH LUNG REGIONS CHARACTERIZAITON. . . . . . . . . . . . . . . . . . 1149Tatjana Zrimec, Sata Busayarat, University of New South Wales, Australia; and Peter Wilson, Pittwater Radiology,Australia

A STATE SPACE APPROACH TO NOISE REDUCTION OF 3D FLUORESCENT MICROSCOPY IMAGES . . 1153Raimund Ober, Xuming Lai, University of Texas at Dallas, USA; Zhiping Lin, Nanyang Technological University,Singapore; and Sally Ward, University of Texas Southwestern Medical Center, USA

AUTOMATIC EXTRACTION OF SEMANTIC CONCEPTS IN MEDICAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . 1157Mira Park and Kotagiri Ramamohanarao, The University of Melbourne, Australia

SESSION TA-S2: Image Forensics

ON INFORMATION HIDING WITH INCOMPLETE INFORMATION ABOUT STEGANALYSIS. . . . . . . . . . . . 1161Rajarathnam Chandramouli, Stevens Institute of Technology, USA

STEGANALYSIS OF QUANTIZATION INDEX MODULATION DATA HIDING . . . . . . . . . . . . . . . . . . . . . . . . . . . 1165Kenneth Sullivan, Zhiqiang Bi, Upamanyu Madhow, Shivkumar Chandrasekaran and B.S. Manjunath, Dept. ofECE, Univ. of Calif., Santa Barbara, USA

A MODEL FOR IMAGE SPLICING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1169Tian-Tsong Ng and Shih-Fu Chang, Department of Electrical Engineering, Columbia University, New York, USA

A STOCHASTIC QIM ALGORITHM FOR ROBUST, UNDETECTABLE IMAGE WATERMARKING. . . . . . . . 1173Pierre Moulin and Alexia Briassouli, University of Illinois, USA

SESSION TA-L1: Feature-based Image Segmentation

CORRIDOR SCISSORS: A SEMI-AUTOMATIC SEGMENTATION TOOL EMPLOYING MINIMUM-COSTCIRCULAR PATHS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1177Dirk Farin, Technische Universiteit Eindhoven, The Netherlands; Magnus Pfeffer, University Mannheim, Ger-many; Peter De With, Technische Universiteit Eindhoven, The Netherlands; and Wolfgang Effelsberg, UniversityMannheim, Germany

SKCS - SEPARABLE KERNEL FAMILY WITH COMPACT SUPPORT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1181Ezzedine Ben Braiek, ESSTT, Tunisia; and Mohamed Cheriet, ETS, Canada

AUTOMATIC GENERATION OF PEN-AND-INK DRAWINGS FROM PHOTOS . . . . . . . . . . . . . . . . . . . . . . . . . . . 1185Jiatao Song, The Hong Kong Polytechnic University, Hong Kong; Zhejiang University, Hangzhou 310027, P.R. China, Hong Kong; Zheru Chi, The Hong Kong Polytechnic University, Hong Kong, Hong Kong; Jilin Liu,Zhejiang University, Hangzhou 310027, P. R. China, China; and Hong Fu, The Hong Kong Polytechnic University,Hong Kong, Hong Kong

A UNIFIED ADAPTIVE APPROACH TO ACCURATE SKIN DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1189Qiang Zhu, ECE, UCSB, USA; Ching-Tung Wu, CS, UCSB, USA; and Kwang-Ting (Tim) Cheng, ECE, UCSB,USA

AN INFORMATION THEORETIC FRAMEWORK FOR IMAGE SEGMENTATION . . . . . . . . . . . . . . . . . . . . . . . . 1193Jaume Rigau, Miquel Feixas and Mateu Sbert, Institut d’Informatica i Aplicacions, Spain

TEXTURE ANALYSIS USING ADAPTIVE BIORTHOGONAL WAVELET PACKETS . . . . . . . . . . . . . . . . . . . . . . 1197G. C. K. Abhayaratne, Electronic Engineering, Queen Mary, University of London, UK; Ian H. Jermyn and JosianeZerubia, INRIA, Sophia Antipolis, France

MODULATION-FEATURE BASED TEXTURED IMAGE SEGMENTATION USING CURVE EVOLUTION. . 1201Iasonas Kokkinos, Georgios Evangelopoulos and Petros Maragos, National Technical University of Athens, Greece

DECOMPOSITION OF RANGE IMAGES USING MARKOV RANDOM FIELDS . . . . . . . . . . . . . . . . . . . . . . . . . . 1205Andreas Pichler, Profactor Produktionsforschung Gmbh., Austria; Robert B. Fisher, School of Informatics, Uni-versity of Edinburgh, UK; and Markus Vincze, Automation and Control Institute, Austria

SESSION TA-L2: Denoising and Deblurring

NOISE REDUCTION OF IMAGES WITH MULTIPLE SUBBAND TRANSFORMS . . . . . . . . . . . . . . . . . . . . . . . . . 1209Toshihisa Tanaka, Tokyo University of Agriculture and Technology, Japan; and Laurent Duval, IFP, France

GEOMETRICAL IMAGE DENOISING USING QUADTREE SEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1213Rahul Shukla and Martin Vetterli, Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland

FULL BLIND DENOISING THROUGH NOISE COVARIANCE ESTIMATION USING GAUSSIAN SCALEMIXTURES IN THE WAVELET DOMAIN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1217Javier Portilla, Universidad de Granada, Spain

MOTION-COMPENSATED TEMPRAL PRE-FILTERING FOR NOISE REDUCTION IN A VIDEO ENCODER 1221Byung Cheol Song and Kang Wook Chun, Digital Media R&D Center, Samsung Electronics Co., Ltd, Republic ofKorea

ASTROPHYSICAL IMAGE DENOISING USING BIVARIATE ISOTROPIC CAUCHY DISTRIBUTIONS INTHE UNDECIMATED WAVELET DOMAIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1225Alin Achim, Diego Herranz and Ercan Kuruoglu, Istituto di Scienza e Tecnologie dell’Informazione, Italy

A NOISY CHAOTIC NEURAL NETWORK APPROACH TO IMAGE DENOISING . . . . . . . . . . . . . . . . . . . . . . . . . 1229Leipo Yan, Lipo Wang and Kim-Hui Yap, Nanyang Technological University, Singapore

FAST RELATIVE NEWTON ALGORITHM FOR BLIND DECONVOLUTION OF IMAGES . . . . . . . . . . . . . . . . 1233Alexander Bronstein, Michael Bronstein, Michael Zibulevsky and Yehoshua Zeevi, Technion - Israel Institute ofTechnology, Israel

SHARPENING-DEMOSAICKING METHOD FOR REMOVAL OF IMAGE BLURS CAUSED BY ANOPTICAL LOW-PASS FILTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1237Takashi Komatsu and Takahiro Saito, Kanagawa University, Japan

SESSION TA-L3: Biometrics II

FINGERPRINT IMAGE QUALITY ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1241Eyung Lim, Centre for Signal Processing, Singapore; Kar-Ann Toh, Institute for Infocomm Research, Singapore;P.N. Suganthan, Nanyang Technological University, Singapore; Xudong Jiang and Wei-Yun Yau, Institute for Info-comm Research, Singapore

COMBINING EXCLUSIVE AND CONTINUOUS FINGERPRINT CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . 1245Lifeng Sha and Xiaoou Tang, The Chinese University of Hong Kong, Hong Kong

CHOOSING BEST BASIS IN WAVELET PACKETS FOR FINGERPRINT MATCHING . . . . . . . . . . . . . . . . . . . . . 1249Ke Huang and Selin Aviyente, Michigan State University, USA

FINGERPRINT IMAGE QUALITY ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253Tai Pang Chen, Xudong Jiang and Weiyun Yau, Institute for Infocomm Research, Singapore

RECONSTRUCTION-FREE MATCHING FOR FINGERPRINT SWEEP SENSORS . . . . . . . . . . . . . . . . . . . . . . . . . 1257Peter Morguet, Christian Narr, Henning Lorch, Infineon Technologies AG, Germany; Frank Wallhoff and GerhardRigoll, Munich University of Technology, Germany

CASCADING STATISTICAL AND STRUCTURAL CLASSIFIERS FOR IRIS RECOGNITION . . . . . . . . . . . . . . 1261Zhenan Sun, Yunhong Wang, Tieniu Tan and Jiali Cui, Center for Biometrics Authentication and Testing, NationalLaboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China

RECOGNITION OF HUMAN AND ANIMAL MOVEMENT USING INFRARED VIDEO STREAMS . . . . . . . . 1265Qin Jiang and Cindy Daniell, HRL Laboratories, LLC, USA

A NEW FACIAL EXPRESSION RECOGNITION TECHNIQUE USING 2-D DCT AND K-MEANSALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1269Liying Ma, Concordia University, Canada; Yegui Xiao, Hiroshima Prefectural Women’s University, Japan; K.Khorasani, Concordia University, Canada; and Rabab Ward, University of British Columbia, Canada

SESSION TA-L4: Lossy Image Coding

CURVED WAVELET TRANSFORM AND OVERLAPPED EXTENSION FOR IMAGE CODING . . . . . . . . . . . . 1273Demin Wang, Liang Zhang and Andre Vincent, Communications Research Centre, Canada

UNDER-SAMPLED AND OVER-SAMPLED PRE-/POST-FILTERS FOR BLOCK DCT CODERS . . . . . . . . . . . 1277Chengjie Tu, Windows Digital Media Division, Microsoft Corporation, USA; Trac D. Tran, ECE Department, TheJohns Hopkins University, USA; and Jie Liang, School of Engineering Science, Simon Fraser University, Canada

SPARSE REPRESENTATION OF IMAGES WITH HYBRID LINEAR MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1281Kun Huang, Allen Yang and Yi Ma, University of Illinois, USA

THE SEAMLESSLY MULTIPLEXED EMBEDDED CODEC (SMEC) AND ITS APPLICATION IN IMAGECODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1285Jin Li, Microsoft, USA

IMAGE SET COMPRESSION THROUGH MINIMAL-COST PREDICTION STRUCTURES . . . . . . . . . . . . . . . . 1289Chia-Ping Chen, Chu-Song Chen, Academia Sinica, Taiwan; Kuo-Liang Chung, National Taiwan University ofScience and Technology, Taiwan; Hsueh-I Lu, Academia Sinica, Taiwan; and Gregory Y. Tang, National TaiwanUniversity, Taiwan

JPEG2000-BASED SHAPE ADAPTIVE ALGORITHM FOR THE EFFICIENT CODING OF MULTIPLEREGIONS-OF-INTEREST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1293Mahesh Subedar, Lina Karam, Arizona State University, USA; and Glen Abousleman, General Dynamics C4Systems, USA

A HIGHLY SCALABLE SPECK IMAGE CODER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1297Gui Xie, Japan Advanced Institute of Science and Technology, Japan

SHAPE-ADAPTIVE CODING USING BINARY SET SPLITTING WITH K-D TREES . . . . . . . . . . . . . . . . . . . . . . 1301James Fowler, Mississippi State University, USA

SESSION TA-L5: Wavelet Video Coding and Scalability I

WEIGHTED AVERAGE SPATIO-TEMPORAL UPDATE OPERATOR FOR SUBBAND VIDEO CODING . . . . 1305Christophe Tillier, Beatrice Pesquet-Popescu, ENST, France; and Mihaela Van der Schaar, Univ. California Davis,USA

ACCURACY-SCALABLE MOTION CODING FOR EFFICIENT SCALABLE VIDEO COMPRESSION . . . . . . 1309Guillaume Boisson, Edouard Francois, Thomson R&D, France; and Christine Guillemot, IRISA, France

BIDIMENSIONAL DICTIONARY AND CODING SCHEME FOR A VERY LOW BITRATE MATCHINGPURSUIT VIDEO CODER. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1313Fulvio Moschetti, Kazuo Sugimoto, Sadaatsu Kato and Minoru Etoh, NTT DoCoMo, USA

AN INVESTIGATION OF 3D DUAL-TREE WAVELET TRANSFORM FOR VIDEO CODING . . . . . . . . . . . . . . 1317Beibei Wang, Yao Wang, Ivan Selesnick, Polytechnic University, USA; and Anthony Vetro, Mitsubishi ElectricResearch Lab, USA

SCALABLE MOTION VECTOR CODING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1321Joeri Barbarien, Adrian Munteanu, Fabio Verdicchio, Yiannis Andreopoulos, Jan Cornelis and Peter Schelkens,Vrije Universiteit Brussel, Belgium

SPATIAL SCALABILITY AND COMPRESSION EFFICIENCY WITHIN A FLEXIBLE MOTIONCOMPENSATED 3D-DWT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1325Nagita Mehrseresht and David Taubman, The University of New South Wales, Australia

AN EFFICIENT CONTENT-ADAPTIVE MC 3D-DWT WITH ENHANCED SPATIAL AND TEMPORALSCALABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1329Nagita Mehrseresht and David Taubman, The University of New South Wales, Australia

SCALABLE CODING OF VARIABLE-SIZE MOTION VECTOR BLOCKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1333Davide Maestroni, Augusto Sarti, Marco Tagliasacchi and Stefano Tubaro, DEI - Politecnico di Milano, Italy

SESSION TA-P1: Stereoscopic and 3-D Processing I

FAST MODEL BASED STEREO MATCHING USING SOAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1337Yusuf Ozturk and Arvind Sridharan, San Diego State University, USA

A SIMILARITY-BASED ADAPTIVE NEIGHBORHOOD METHOD FOR CORRELATION-BASED STEREOMATCHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1341Madain Perez, Pierre Bonnet, Olivier Colot and Francois Cabestaing, USTL, France

ADAPTIVE STEREO MATCHING ALGORITHM BASED ON EDGE DETECTION . . . . . . . . . . . . . . . . . . . . . . . . 1345Kun Wang, The Institute of Artificial Intelligence and Robotics, China

CAMERA CALIBRATION WITHOUT METRIC INFORMATION USING 1D OBJECTS . . . . . . . . . . . . . . . . . . . . 1349Xiaochun Cao and Hassan Foroosh, University of Central Florida, USA

STEREO-BASED HUMAN HEAD DETECTION FROM CROWD SCENES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1353Xiaoyu Huang, Liyuan Li, Institute for Infocomm Research, Singapore; and Terence Sim, National University ofSingapore, Singapore

UNCALIBRATED STEREO RECTIFICATION FOR AUTOMATIC 3D SURVEILLANCE . . . . . . . . . . . . . . . . . . . 1357Ser-Nam Lim, Larry Davis, Univ. of Maryland, College Park, CS dept., USA; Anurag Mittal, Siemens CorporateResearch, Princeton, USA; and Nikos Paragios, Ecole Nationale de Ponts et Chaussees, France

ROBUST BAYESIAN CAMERA MOTION ESTIMATION USING RANDOM SAMPLING . . . . . . . . . . . . . . . . . . 1361Gang Qian, Arizona State University, USA; Rama Chellappa and Qinfen Zheng, University of Maryland, USA

SHAPE RECONSTRUCTION FOR COLOR OBJECTS USING SEGMENTATION AND PHOTOMETRICSTEREO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1365Osamu Ikeda, Takushoku University, Japan

A ROBUST METHOD FOR RECOVERING GEOMETRIC PROXY FROM MULTIPLE PANORAMICIMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1369Ada S. K. Wan, Angus M. K. Siu, Rynson W. H. Lau and C. W. Ngo, City University of Hong Kong, Hong Kong

DISPARITY ESTIMATION USING COLOR COHERENCE AND STOCHASTIC DIFFUSION. . . . . . . . . . . . . . . 1373Sang Hwa Lee, Nam Ik Cho, Seoul National University, South Korea; and Jong-il Park, Hanyang University, SouthKorea

EFFECTIVE INTERPOLATION FOR FREE VIEWPOINT IMAGES USING MULTI-LAYERED DYNAMICBACKGROUND BUFFERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1377Atsushi Matsumura, Sei Naito, Ryoichi Kawada, Atsushi Koike and Shuichi Matsumoto, KDDI R&D LaboratoriesInc., Japan

BUILDING BLOCKS FOR AUTONOMOUS NAVIGATION USING CONTOUR CORRESPONDENCES . . . . . 1381M. Pawan Kumar, C. V. Jawahar and P. J. Narayanan, CVIT, IIIT, India

SESSION TA-P2: Face Detection, Recognition and Classification II

NAIVE BAYES FACE/NONFACE CLASSIFIER: A STUDY OF PREPROCESSING AND FEATUREEXTRACTION TECHNIQUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1385Son Lam Phung, Abdesselam Bouzerdoum, Douglas Chai and Anthony Watson, Edith Cowan University, Australia

REFLECTANCE CORRECTION FOR PERSPIRING FACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1389William Smith, Antonio Robles-Kelly and Edwin Hancock, University of York, UK

A ROBUST FEATURE EXTRACTION FRAMEWORK FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . 1393Guang Dai and Yuntao Qian, College of Computer Science, Zhejiang University, China

SELF QUOTIENT IMAGE FOR FACE RECOGNITION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1397Haitao Wang, Institute of Automation, Chinese Academy of Sciences, China; Stan Z. Li, Microsoft Research Asia,China; Yangsheng Wang, Institute of Automation, Chinese Academy of Sciences, China; and Jian J. Zhang, NCCA,Media School, Bournemouth University, UK

FACE IDENTIFICATION FROM ONE SINGLE SAMPLE FACE IMAGE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1401Hung-Son Le and Haibo Li, Dept. of Applied Physics and Electronics, Umea University, Sweden

FACIAL EVENT MINING USING COUPLED HIDDEN MARKOV MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1405Limin Ma, Qiang Zhou, Mehmet Celenk and David Chelberg, Ohio University, USA

FACIAL EXPRESSION ANALYSIS BY KERNEL EIGENSPACE METHOD BASED ON CLASS FEATURES(KEMC) USING NON-LINEAR BASIS FOR SEPARATION OF EXPRESSION-CLASSES . . . . . . . . . . . . . . . . . . 1409Yohei Kosaka and Kazunori Kotani, School of Information Science, Japan Advanced Institute of Science and Tech-nology, Japan

FACE DETECTION TECHNIQUE BASED ON INTESITY AND SKIN COLOR DISTRIBUTION . . . . . . . . . . . . 1413Satyanadh Gundimada, Li Tao and Vijayan Asari, Old Dominion University, USA

FUSION OF SVD AND LDA FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1417Yanwei Pang, Rong Zhang, Zhengkai Liu, Microsoft-USTC Intelligent Computing Research Center, China; Neng-hai Yu, University of Science and Technology of China, China; and Jiawei Rong, Fudan University, China

THREE-DIMENSIONAL FACE RECOGNITION: AN EIGENSURFACE APPROACH . . . . . . . . . . . . . . . . . . . . . . . 1421Thomas Heseltine, Nick Pears and Jim Austin, The University of York, Britain

FAST FACIAL FEATURE EXTRACTION USING A DEFORMABLE SHAPE MODEL WITHHAAR-WAVELET BASED LOCAL TEXTURE ATTRIBUTES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1425Fei Zuo, Eindhoven University of Technology, The Netherlands; and Peter De With, Eindhoven Univ. of Technol. /LogicaCMG, The Netherlands

CURVATURE BASED HUMAN FACE RECOGNITION USING DEPTH WEIGHTED HAUSDORFFDISTANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1429Yeung-Hak Lee, Yeungnam University, South Korea; and Jae-Chang Shim, Andong National University, SouthKorea

FACIAL RECOGNITION AND VERIFICATION USING GABOR WAVELETS AND KERNEL METHODS . . 1433Li Bai, Nottingham University, UK; Linlin Shen, University of Nottingham, UK; and Phil Picton, University Col-lege Northampton, UK

PEOPLE MONITORING USING FACE RECOGNITION WITH OBSERVATION CONSTRAINTS . . . . . . . . . . . 1437Ji Tao and Yap-Peng Tan, Nanyang Technological University, Singapore

SESSION TA-P3: Motion Detection and Estimation: Block Matching

A MULTISTAGE FAST MOTION ESTIMATION SCHEME FOR VIDEO COMPRESSION . . . . . . . . . . . . . . . . . . 1441Jiancong Luo, Ishfaq Ahmad, Yu Sun and Yongfang Liang, The University of Texas at Arlington, USA

FAST BLOCK-MATCHING MOTION ESTIMATION BY RECENT-BIASED SEARCH FOR MULTIPLEREFERENCE FRAMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1445Chi-Wang Ting, Wing-Hong Lam and Lai-Man Po, City University of Hong Kong, Hong Kong

SHORT/LONG-TERM MOTION VECTOR PREDICTION IN MULTI-FRAME VIDEO CODING SYSTEM. . . 1449Yi-Hon Hsiao, Tien-Hsu Lee and Pao-Chi Chang, Department of Electrical Engineering, National Central Univer-sity, Taiwan

SEARCH WINDOW SIZE DECISION FOR MOTION ESTIMATION ALGORITHM IN H.264 VIDEO CODER 1453Gianluca Bailo, Massimo Bariani, Ivano Barbieri and Marco Raggio, Dibe - University of Genova, Italy

ADAPTIVE BLOCK SUB-SAMPLING ALGORITHM FOR MOTION-ESTIMATION ON SIMDPROCESSORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1457Munish Jindal and Nageswara Rao G., Emuzed India Pvt. Ltd., India

COMBINED 3D OBJECT MOTION ESTIMATION IN MEDICAL SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1461Delhay Bertrand, Clarysse Patrick, CREATIS, France; Grangeat Pierre, CEA-LETI, France; Magnin Isabelle,CREATIS, France; and Bonnet Stephane, CEA-LATI, France

RECURSIVE TEMPORAL DENOISING AND MOTION ESTIMATION OF VIDEO . . . . . . . . . . . . . . . . . . . . . . . . 1465Vladimir Zlokolica, Aleksandra Pizurica and Wilfried Philips, TELIN, University of Ghent, Belgium

AN ADAPTIVE MOTION ESTIMATION ALGORITHM BASED ON EVOLUTION STRATEGIES WITHCORRELATED MUTATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1469Wang Hui and Mao Zhigang, Harbin Institute of Technology Microelectronics Center 313, China

NOVEL FRAME INTERPOLATION METHOD FOR HOLD-TYPE DISPLAYS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1473Nao Mishima and Goh Itoh, Multimedia Laboratory, Corporate Research & Develop Center, Toshiba Corp., Japan

A NOVEL FLATTED HEXAGON SEARCH PATTERN FOR FAST BLOCK MOTION ESTIMATION . . . . . . . . 1477Thou-Ho (Chao-Ho) Chen and Yi-Fan Li, Department of Electronic Engineering, National Kaohsiung Universityof Applied Sciences, Taiwan

A TWO STAGE VARIABLE BLOCK SIZE MOTION SEARCH ALGORITHM FOR H.264 ENCODER . . . . . . . 1481Tomoyuki Shimizu, Akio Yoneyama, Hiromasa Yanagihara and Yasuyuki Nakajima, KDDI R&D Laboratories Inc.,Japan

FAST FULL SEARCH BLOCK MOTION ESTIMATION FOR H.264/AVC WITH MULTILEVELSUCCESSIVE ELIMINATION ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1485Tuukka Toivonen and Janne Heikkila, University of Oulu, Finland

FUZZY NON-RIGID MOTION ESTIMATION ROBUST TO ROTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1489Juan Morales Sanchez, Rafael Verdu Monedero, Ricardo Gonzalez Leon, Universidad Politecnica de Cartagena,Spain; and Luis Weruaga Prieto, Austrian Academy of Sciences, Austria

SESSION TA-P4: Feature Extraction and Analysis: Color and Texture

TEXTURE DISCRIMINATION USING MULTIMODAL WAVELET PACKET SUBBANDS . . . . . . . . . . . . . . . . . 1493Roberto Cossu, Ian Jermyn and Josiane Zerubia, INRIA, France

COMPARISON OF LINEAR SPECTRAL RECONSTRUCTION METHODS FOR MULTISPECTRALCOLOUR IMAGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1497David Connah, Jon Hardeberg, Gjøvik University College, Norway; and Stephen Westland, Leeds University,England

OBJECT TRACKING BY ADAPTIVE FEATURE EXTRACTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1501Bohyung Han and Larry Davis, University of Maryland-College Park, USA

COLOR TEXTURAL FEATURES UNDER VARYING ILLUMINATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1505Dimitrios Iakovidis, Univ. of Athens, Greece; Dimitrios Maroulis, Univ. of t Athens, Greece; and Stavros Karkanis,Technological Inst. of Lamia, Greece

ADVANCES IN TEXTURE ANALYSIS: ENERGY DOMINANT COMPONENT & MULTIPLE HYPOTHESISTESTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1509Iasonas Kokkinos, Georgios Evangelopoulos and Petros Maragos, National Technical University of Athens, Greece

A FAST PROCEDURE FOR THE COMPUTATION OF SIMILARITIES BETWEEN GAUSSIAN HMMS . . . . . 1513Ling Chen and Hong Man, Stevens Institute of Technology, USA

MULTISCALE ASYMMETRY SIGNATURES FOR TEXTURE ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1517Gert Van de Wouwer, Visielab, University of Antwerp, Belgium; Barbara Weyn and Dirk Van Dyck, University ofAntwerp, Belgium

A NEW SVM KERNEL FOR TEXTURE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1521Mahdi Sabri and Javad Alirezaie, Ryerson University, Canada

A MEASURE FOR SPATIAL DEPENDENCE IN NATURAL STOCHASTIC TEXTURES . . . . . . . . . . . . . . . . . . . 1525Roberto Costantini, Ecole Polytechnique Federale de Lausanne, Switzerland; Gloria Menegaz, University of Siena,Italy; and Sabine Susstrunk, Ecole Polytechnique Federale de Lausanne, Switzerland

SEQUENTIAL UPDATING ALGORITHM FOR EXTRACTING THE BASIS OF THE KARHUNEN-LOEVETRANSFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1529Yanyun Qu, Department of Computer Science of Xiamen University, China; Nanning Zheng, Zejian Yuan, Insti-tute of Artificial Intelligence and Robotics of Xi’an Jiaotiong University, China; and Cuihua Li, Department ofComputer Science of Xiamen University, China

A NEW PALETTE HISTOGRAM SIMILARITY MEASURE FOR MPEG-7 DOMINANT COLORDESCRIPTOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1533Lai-Man Po and Ka-Man Wong, City University of Hong Kong, Hong Kong

TEXTURE SIMILARITY EVALUATION USING ORDINAL CO-OCCURRENCE . . . . . . . . . . . . . . . . . . . . . . . . . . 1537Mari Partio, Bogdan Cramariuc and Moncef Gabbouj, Tampere University of Technology, Finland

A COMPARISON OF THE OCTAVE-BAND DIRECTIONAL FILTER BANK AND GABOR FILTERS FORTEXTURE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1541Paul Hong, Georgia Institute of Technology, USA; Lance Kaplan, Clark Atlanta University, USA; and Mark Smith,Purdue University, USA

ROTATION INVARIANT TEXTURE CLASSIFICATION USING DIRECTIONAL FILTER BANK ANDSUPPORT VECTOR MACHINE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1545Hong Man, Ling Chen and Rong Duan, Stevens Institute of Technology, USA

SESSION TA-P5: Watermarking III

PREDICTION-ERROR BASED REVERSIBLE WATERMARKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1549Diljith Thodi and Jeffrey Rodriguez, The University of Arizona, USA

AN IMAGE NORMALIZATION BASED WATERMARKING SCHEME ROBUST TO GENERAL AFFINETRANSFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1553Hwan Il Kang, Myongji University, South Korea; and Edward Delp, Purdue University, USA

DATA HIDING IN JPEG 2000 CODE STREAMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1557Wei Liu, Panasonic R&D Center China Co. Ltd., China

SINR, BIT ERROR RATE, AND SHANNON CAPACITY OPTIMIZED SPREAD-SPECTRUMSTEGANOGRAPHY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1561Maria Gkizeli, Dimitris Pados, State University of New York at Buffalo, USA; and Michael Medley, SUNY Instituteof Technology, USA

A SUITABLE IMAGE HIDING SCHEME FOR JPEG IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1565Shinfeng D. Lin, Shih-Chieh Shie and Chung-Chien Chou, Dept. of Computer Science and Information Engineer-ing, National Dong Hwa University., Taiwan

A BLIND ROBUST WATERMARKING SCHEME FOR COPYRIGHT PROTECTION OF 3D MESH MODELS 1569Stefanos Zafeiriou, Anastasios Tefas and Ioannis Pitas, Department of Informatics Aristotle University of Thessa-loniki, Greece

A SECURE IMAGE AUTHENTICATION ALGORITHM WITH PIXEL-LEVEL TAMPER LOCALIZATION. . 1573Jinhai Wu, Tsinghua Univ., China; Bin Zhu, Shipeng Li, Microsoft Research Asia, China; and Fuzong Lin, Ts-inghua Univ., China

3D MESH WATERMARKING USING PROJECTION ONTO CONVEX SETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1577Suk-Hwan Lee, Tae-Su Kim, Seung-Jin Kim, School of Electrical Engineering & Computer Science, KyungpookNational University, Republic of Korea; Young Huh, Korea Electrotechnology Research Institute, Republic ofKorea; Ki-Ryong Kwon, Department of Electronic Engineering, Pusan University of Foreign Studies, Republic ofKorea; and Kuhn-Il Lee, School of Electrical Engineering & Computer Science, Kyungpook National University,Republic of Korea

A NEW ALGORITHM FOR COLLUSION RESISTANT VIDEO WATERMARKING . . . . . . . . . . . . . . . . . . . . . . . . 1581Vinod P and P K Bora, Department of ECE, IIT Guwahati, India

SESSION TA-P6: Video Indexing, Retrieval and Editing

GENERIC SLOW-MOTION REPLAY DETECTION IN SPORTS VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1585Lei Wang, Xu Liu, Tsinghua University, China; Steve Lin, Microsoft Research Asia, China; Guangyou Xu, TsinghuaUniversity, China; and Heung-Yeung Shum, Microsoft Research Asia, China

ABRUPT AND GRADUAL SCENE TRANSITION DETECTION IN MPEG-4 COMPRESSED VIDEOSEQUENCES USING TEXTURE AND MACROBLOCK INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1589W. Anil Chandana Fernando and Kok-Keong Loo, Brunel University, UK

REAL-TIME TEMPORAL TEXTURE CHARACTERISATION USING BLOCK-BASED MOTIONCO-OCCURRENCE STATISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1593Ashfaqur Rahman and Manzur Murshed, Monash University, Australia

MEAN SHIFT BASED NONPARAMETRIC MOTION CHARACTERIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1597Ling-Yu Duan, Min Xu, Qi Tian and Chang-Sheng Xu, Institute for Infocomm Research, Singapore

FAST VIDEO SHOT RETRIEVAL BY TRACE GEOMETRY MATCHING IN PRINICIPAL COMPONENTSPACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1601Zhu Li, Motorola Labs, Schaumburg, USA; Aggelos Katsaggelos, Northwestern University, Evanston, USA; andBhavan Gandhi, Motorola Labs, Schaumburg, USA

AUTOMATICALLY LEARNING STRUCTURAL UNITS IN EDUCATIONAL VIDEOS WITH THEHIERARCHICAL HIDDEN MARKOV MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1605Dinh Phung, Svetha Venkatesh, Curtin University of Technology, Australia; and Hung Bui, AI Center, SRI Interna-tional, USA

ENHANCING LATENT SEMANTIC ANALYSIS VIDEO OBJECT RETRIEVAL WITH STRUCTURALINFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1609Fabrice Souvannavong, Lukas Holh, Bernard Merialdo and Benoit Huet, EURECOM, France

CONTENT AND TRANSFORMATION EFFECT MATCHING FOR AUTOMATED HOME VIDEO EDITING 1613Xian-Sheng Hua and Hong-Jiang Zhang, Microsoft Research Asia, China

TIME-CONSTRAINT BOOST FOR TV COMMERCIALS DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1617Tie-Yan Liu, Microsoft Research Asia, China; Tao Qin, Dept. Electronic Engineering, Tsinghua University, China;and Hong-Jiang Zhang, Microsoft Research Asia, China

SEMANTIC UNITS BASED EVENTS DETECTION IN SOCCER VIDEOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1621Xiaofeng Tong, Qingshan Liu and Hanqing Lu, National Laboratory of Pattern Recognition, Institute of Automa-tion, Chinese Academy of Sciences, China

HIGH-LEVEL SOCCER INDEXING ON LOW-LEVEL FEATURE SPACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1625Masaru Sugano, KDDI R&D Laboratories Inc., Japan; Koichi Uemura, Science University of Tokyo, Japan; Ya-suyuki Nakajima and Hiromasa Yanagihara, KDDI R&D Laboratories Inc., Japan

GOAL DETECTION IN SOCCER VIDEO USING AUDIO VISUAL KEYWORDS . . . . . . . . . . . . . . . . . . . . . . . . . . 1629Yu-Lin Kang, Joo-Hwee Lim, Institute for Infocomm Research, Singapore; Mohan Kankanhalli, National Univer-sity of Singapore, Singapore; Changsheng Xu and Qi Tian, Institute for Infocomm Research, Singapore

A SOCCER FIELD TRACKING METHOD WITH WIRE FRAME MODEL FROM TV IMAGES . . . . . . . . . . . . . 1633Tomoki Watanabe, Miki Haseyama and Hideo Kitajima, School of Engineering, Hokkaido University, Japan

EVENT DETECTION BASED ON NON-BROADCAST SPORTS VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1637Jinjun Wang, Changsheng Xu, Institute for Infocomm Research, Singapore; Engsiong Chn, Nanyang TechnologicalUniversity, Singapore; Xinguo Yu and Qi Tian, Institute for Infocomm Research, Singapore

SESSION TA-P7: Interpolation

MMSE RECONSTRUCTION FOR 3D ULTRASOUND IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1641Wei Huang, Yibin Zheng and Janelle A. Molloy, University of Virginia, USA

QUANTITATIVE ANALYSIS OF RESOLUTION SYNTHESIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1645Ramez Yoakeim and David Taubman, University of New South Wales, Australia

NOISE REDUCTION AND INTERLACED-TO-PROGRESSIVE CONVERSION BASED ON OPTIMALADAPTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1649Seungjoon Yang, Jae-Han Jung and You-Young Jung, Samsung Electronics Co., Ltd, Korea

GENERIC METHOD FOR 2D IMAGE RESIZING WITH NON-SEPARABLE FILTERS . . . . . . . . . . . . . . . . . . . . . 1653Christian Hentschel, Brandenburg University of Technology Cottbus, Germany

A NORMALIZED MODEL FOR COLOR-RATIO BASED DEMOSAICKING SCHEMES . . . . . . . . . . . . . . . . . . . 1657Rastislav Lukac and Konstantinos Plataniotis, University of Toronto, Canada

LARGE-SCALE INFOGRAPHIC IMAGE DOWNSIZING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1661Ruihua Ma, Institute of Infocomm Research, (I2R), Singapore; and Gurminder Singh, Naval Postgraduate School,USA

USING NATURAL IMAGE PROPERTIES AS DEMOSAICING HINTS.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1665Ido Omer and Michael Werman, HUJI, Israel

ROBUST CORRECTION STEP FOR CFA INTERPOLATION SCHEMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1671Rastislav Lukac, Karl Martin, Konstantinos Plataniotis, University of Toronto, Canada; and Bogdan Smolka,Silesian University of Technology, Poland

IMAGE MORPHING BASED ON MUTUAL INFORMATION AND OPTIMAL MASS TRANSPORT . . . . . . . . 1675Lei Zhu, Yan Yang, Allen Tannenbaum, Georgia Institute of Technology, USA; and Steven Haker, Brigham andWomen’s Hospital and Harvard Medical School, USA

A RECURSIVE APPROACH FOR DE-INTERLACING USING IMPROVED ELA AND MOTIONCOMPENSATION BASED ON BI-DIRECTIONAL BMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1679Seungchan Byun, Jeongmoon Byun and Gyeonghwan Kim, Sogang University, South Korea

MULTI-LEVEL FAST MULTIPOLE METHOD FOR THIN PLATE SPLINE EVALUATION . . . . . . . . . . . . . . . . . 1683Ali Zandifar, Ser-Nam Lim, Ramani Duraiswami, Nail A. Gumerov and Larry S. Davis, University of Maryland,USA

IMAGE INTERPOLATION BASED ON INTER-SCALE DEPENDENCY IN WAVELET DOMAIN . . . . . . . . . . . 1687Dong Hun Woo, Dept. Electronic Eng. Pusan National University, South Korea; Il Kyu Eom, Dept. Informationand Communicatio Eng. Miryang National University, South Korea; and Yoo Shin Kim, Dept. Electronic Eng.Pusan National University, South Korea

SESSION TA-P8: Geosciences and Remote Sensing and Environment

MULTISCALE SEGMENTATION OF TEXTURED SONAR IMAGES USING COOCCURRENCESTATISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1691Imen Karoui, Jean-Marc Boucher, ENST-Bretagne, France; Ronan Fablet and Jean-Marie Augustin, IFREMER,France

GENERATION OF VIDEO METADATA SUPPORTING VIDEO-GIS INTEGRATION. . . . . . . . . . . . . . . . . . . . . . . 1695In-Hak Joo, Tae-Hyun Hwang and Kyung-Ho Choi, Electronics and Telecommunications Research Institute, SouthKorea

ELEVATION CONTOURS EXTRACTION FROM A COLOR-CODED RELIEF SCANNED MAP . . . . . . . . . . . . 1699Carol Rus, Corneliu Rusu, Technical University of Cluj-Napoca, Romania; and Jaakko Astola, Tampere Interna-tional Center for Signal Processing, Finland

A REGION-BASED METHOD FOR GRAPH TO IMAGE REGISTRATION WITH AN APPLICATION TOCADASTRE DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1703Roger Trias-Sanz and Marc Pierrot-Deseilligny, Institut Geographique National, France

AN EARLY FIRE-DETECTION METHOD BASED ON IMAGE PROCESSING . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1707Thou-Ho (Chao-Ho) Chen, Ping-Hsueh Wu and Yung-Chuen Chiou, Department of Electronic Engineering, Na-tional Kaohsiung University of Applied Sciences, Taiwan

A NOVEL TWOCSTEP STRATEGY FOR AUTOMATIC GIS-IMAGE REGISTRATION . . . . . . . . . . . . . . . . . . . . 1711Zhanwu Yu, National Laboratory of Pattern Recognition,IOA,CAS, China; Veronique Prinet and Chunhong Pan,National Laboratory of Pattern Recongition,IOA,CAS, China

NOVEL AIRCRAFT TYPE RECOGNITION WITH LEARNING CAPABILITIES IN SATELLITE IMAGES . . 1715JunWei Hsieh, Department of Electrical Engineering, Yuan Ze University, Taiwan; Jian-Ming Chen, Chi-HungChuang and KaoCHin Fan, Department of Computer Engineering, National Central University, Taiwan

A LAND USE CLASSIFICATION METHOD BASED ON REGION AND EDGE INFORMATION FUSION . . 1719Gang Wu, Chunhong Pan, Veronique Prinet and Songde Ma, National Laboratory of Pattern Recognition,Instituteof Automation, Chinese Academy of Sciences, China

SEMI-AUTOMATIC ROAD DETECTION FROM SATELLITE IMAGERY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1723Somkait Udomhunsakul, King Mongkut’s Institute of Technology Ladkrabang, Thailand

TOWARDS COMPUTER-ASSISTED PHOTO-IDENTIFICATION OF HUMPBACK WHALES . . . . . . . . . . . . . . 1727Elena Ranguelova, Mark Huiskes and Eric Pauwels, CWI, The Netherlands

BUILDING EDGE DETECTION BASED ON DYADIC WAVELET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1731Qiming Qin, Institute of Rs&GIS, Peking University, China; Wenjun Wang, Department of Communication Engi-neering, Yanshan University, China; and Sijin Chen, Institute of Rs&GIS, Peking University, China

SESSION TP-S1: What is the Latest in Networked Video?

OPTIMAL ERASURE PROTECTION FOR SCALABLY COMPRESSED VIDEO STREAMS WITH LIMITEDRETRANSMISSION ON CHANNELS WITH IID AND BURSTY LOSS CHARACTERISTICS . . . . . . . . . . . . . . 1735Johnson Thie and David Taubman, The University of New South Wales, Australia

VIDEOCONFERENCING OVER AN INTERMEDIATE-PROXY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1739Ali C. Begen and Yucel Altunbasak, Georgia Institute of Technology, USA

TRANSMISSION PROTOCOLS FOR STREAMING VIDEO OVER WIRELESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1743Minghua Chen and Avideh Zakhor, EECS, UC Berkeley, USA

OVERLAY AND PEER-TO-PEER MULTICAST WITH NETWORK-EMBEDDED FEC . . . . . . . . . . . . . . . . . . . . . 1747Hayder Radha and Mingquan Wu, Michigan State University, USA

MINIMIZING DISTORTION FOR MULTI-PATH VIDEO STREAMING OVER AD HOC NETWORKS . . . . . . 1751Eric Setton, Xiaoqing Zhu and Bernd Girod, Stanford University, USA

SCALABLE PREDICTIVE CODING BY NESTED QUANTIZATION WITH LAYERED SIDE INFORMATION 1755Huisheng Wang and Antonio Ortega, Signal and Image Processing Institute, Department of Electrical Engineering,University of Southern California, USA

A PEER-TO-PEER VIDEO-ON-DEMAND SYSTEM USING MULTIPLE DESCRIPTION CODING ANDSERVER DIVERSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1759Xiaofeng Xu, Yao Wang, Shivendra Panwar and Keith Ross, Polytechnic University, USA

SECURE MEDIA STREAMING & SECURE ADAPTATION FOR NON-SCALABLE VIDEO. . . . . . . . . . . . . . . . 1763John Apostolopoulos, HP Labs, USA

SESSION TP-L1: Super-resolution and Interpolation

MOTION COMPENSATED SUPER-RESOLUTION OF VIDEO BY LEVEL SETS EVOLUTION . . . . . . . . . . . . 1767Carlos Vazquez, INRS-EMT, Canada; Hussein Aly, SITE, University of Ottawa, Canada; Eric Dubois, Faculty ofEngineering, University of Ottawa, Canada; and Amar Mitiche, INRS-EMT, Canada

SUPER-RESOLUTION WITH SIGNIFICANT ILLUMINATION CHANGE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1771Wen-Yi Zhao, Sarnoff Corporation, USA

ZOOM BASED SUPER-RESOLUTION THROUGH SAR MODEL FITTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1775M. V. Joshi and Subhasis Chaudhuri, IIT Mumbai, India

HIGH-DIMENSIONAL MUTUAL INFORMATION ESTIMATION FOR IMAGE REGISTRATION . . . . . . . . . . 1779Jan Kybic, Center for Machine Perception, CTU, Czech Republic

IMAGE SCALE AND ROTATION FROM THE PHASE-ONLY BISPECTRUM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1783Janne Heikkila, University of Oulu, Finland

LIGHT FIELD COMPLETION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1787Liron Yatziv, Guillermo Sapiro, University of Minnesota, USA; and Marc Levoy, Standford University, USA

ACCELERATION OF CSRBF-BASED IMAGE RECONSTRUCTION BY WAVELET DOMAINPRECONDITIONING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1791Luis Diago, CUJAE University, Cuba; Masaki Kitago and Ichiro Hagiwara, Tokyo Institute of Technology, Japan

MOTION ESTIMATION IN HIGH RESOLUTION IMAGE RECONSTRUCTION FROM COMPRESSEDVIDEO SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1795Luis D. Alvarez, Rafael Molina, University of Granada, Spain; and Aggelos K. Katsaggelos, Northwestern Uni-versity, USA

SESSION TP-L2: Deblocking, Restoration, and Enhancement

DERINGING AND DEBLOCKING DCT COMPRESSION ARTIFACTS WITH EFFICIENT SHIFTEDTRANSFORMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1799Ramin Samadani, HP Labs, Palo Alto, USA; Arvind Sundararajan, Xilinx corporation, USA; and Amir Said, HPLabs, Palo Alto, USA

ADAPTIVE FUZZY POST-FILTERING FOR HIGHLY COMPRESSED VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1803Hao-Song Kong, Mitsubishi Electric Research Laboratories, USA; Yao Nie, University of Delaware, USA; AnthonyVetro, Huifang Sun, Mitsubishi Electric Research Labs, USA; and Kenneth Barner, University of Delaware, USA

NONLINEAR WARPING FUNCTION RECOVERY BY SCAN-LINE SEARCH USING DYNAMICPROGRAMMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1807Fatih Porikli, MERL, USA

BAYESIAN POSTPROCESSING ALGORITHM FOR DWT-BASED COMPRESSED IMAGE. . . . . . . . . . . . . . . . 1811Wei Wen, Zhiyun Xiao and Silong Peng, National ASIC Design Engineering Center, Institute of Automation, Chi-nese Academy of Sciences, China

OPTIMAL SPARSE REPRESENTATIONS FOR BLIND SOURCE SEPARATION AND BLINDDECONVOLUTION: A LEARNING APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1815Michael Bronstein, Alexander Bronstein, Michael Zibulevsky and Yehoshua Zeevi, Technion - Israel Institute ofTechnology, Israel

PIXEL RECOVERY VIA L1 MINIMIZATION IN THE WAVELET DOMAIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1819Ivan Selesnick, Richard Van Slyke, Polytechnic University, USA; and Onur Guleryuz, DoCoMo USA Laboratories,Inc., USA

AUTOMATED TREATMENT OF FILM TEAR IN DEGRADED ARCHIVED MEDIA. . . . . . . . . . . . . . . . . . . . . . . 1823David Corrigan and Anil Kokaram, Department of Electrical and Electronic Engineering, Trinity College Dublin,Ireland

CORRECTION OF UNDEREXPOSED IMAGES USING SCENE RADIANCE ESTIMATION . . . . . . . . . . . . . . . 1827Antonio Robles-Kelly and Edwin Hancock, The University of York, UK

SESSION TP-L3: Motion Estimation and Detection

AN ADAPTIVE SCHEME FOR ESTIMATING MOTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1831Hassan Foroosh, University of Central Florida, USA

ROBUST OPTICAL FLOW FROM PHOTOMETRIC INVARIANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1835Joost Van de Weijer and Theo Gevers, University of Amsterdam, The Netherlands

AN ACCURATE AND ADAPTIVE OPTICAL FLOW ESTIMATION ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . 1839Chin-Hung Teng, Department of Electrical Engineering, National Tsing Hua University, Taiwan; Shang-HongLai, Department of Computer Science, National Tsing Hua University, Taiwan; Yung-Sheng Chen, Department ofElectrical Engineering, Yuan Ze University, Taiwan; and Wen-Hsing Hsu, Department of Electrical Engineering,National Tsing Hua University, Taiwan

EVOLUTIONARY AGENTS FOR EPIPOLAR GEOMETRY ESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1843Mingxing Hu, Virtual Engineering Centre, Queen’s University Belfast, UK; Gordon Dodds, School of Electrical& Electronic Engineering, Queen’s University Belfast, UK; and Baozong Yuan, Institute of Information Science,Beijing Jiaotong University, China

ADAPTIVE EIGEN-BACKGROUNDS FOR OBJECT DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1847Jonathan Rymel, John-Paul Renno, Darrel Greenhill, Digital Imaging Research Centre, UK; James Orwell andGraeme A. Jones, Kingston University, UK

CYLINDRICAL SENSOR CALIBRATION USING LINES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1851Laurent Smadja, Ryad Benosman and Jean Devars, LISIF, France

MOTION ESTIMATION FROM MOTION SMEAR - A SYSTEM IDENTIFICATION APPROACH . . . . . . . . . . . 1855Om Ji Omer, Sameer Kumar, Indian Institute of Technology, Kanpur, India; Rajeev Bajpai, Emuzed India, India;K. S. Venkatesh and Sumana Gupta, Indian Institute of Technology, Kanpur, India

ANALYSIS OF IMPULSE TRAIN ILLUMINATED IMAGES FOR 2D VELOCITY MEASUREMENT. . . . . . . . 1859Jan Horn, Institut fuer Mess- und Regelungstechnik, Universitaet Karlsruhe (TH), Germany

SESSION TP-L4: Image Segmentation

STATISTICAL SOLUTION TO WATERSHED OVER-SEGMENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1863Valentin Gies and Thierry M. Bernard, ENSTA LEI, France

SEGMENTATION OF REMOTE-SENSING IMAGES BY SUPERVISED TS-MRF . . . . . . . . . . . . . . . . . . . . . . . . . . 1867Giovanni Poggi, Giuseppe Scarpa, Universita di Napoli Federico II, Italy; and Josiane Zerubia, INRIA SophiaAntipolis, France

DENSITY ESTIMATION USING MODIFIED EXPECTATION-MAXIMIZATION ALGORITHM FOR ALINEAR COMBINATION OF GAUSSIANS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1871Aly Farag, Ayman El-Baz, University of Louisville, USA; and Georgy Gimel’ farb, University of Auckland, NewZealand

DEFORMABLE STRUCTURAL MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1875Steven Bergner, Simon Fraser University, Canada; Stephan Al-Zubi and Klaus Tonnies, Otto-von-Guericke Uni-versity, Germany

GAP CLOSURE IN (ROAD) NETWORKS USING HIGHER-ORDER ACTIVE CONTOURS . . . . . . . . . . . . . . . . 1879Marie Rochery, Ian Jermyn and Josiane Zerubia, Ariana (joint research group CNRS/INRIA/UNSA), France

SHAPE ESTIMATION OF 3-D DNA MOLECULES FROM STEREO CRYO-ELECTRON MICRO-GRAPHS . 1883Mathews Jacob, Beckman Institute, UIUC, USA; Thierry Blu and Michael Unser, EPFL, Switzerland

CONTEXT-DEPENDENT TREE-STRUCTURED IMAGE CLASSIFICATION USING THE QDADISTORTION MEASURE AND THE HIDDEN MARKOV MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1887Kivanc Ozonat and SangHo Yoon, Stanford University, USA

REFERENCE LINE APPROACH FOR VECTOR DATA COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1891Alexander Akimov, Alexander Kolesnikov and Pasi Franti, University of Joensuu, Finland

SESSION TP-L5: Biomedical Image Processing: Compression, Registra-tion and Fusion

GENERALIZED SUBSPACE RULES FOR ON-LINE PCA AND THEIR APPLICATION IN SIGNAL ANDIMAGE COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1895Toshihisa Tanaka, Tokyo University of Agriculture and Technology, Japan

A NOVEL PROGRESSIVE THICK SLAB PARADIGM FOR VOLUMETRIC MEDICAL IMAGECOMPRESSION AND NAVIGATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1899Bharath Kumar Sv, Sudipta Mukhopadhyay and Vishram Nandedkar, General Electric-Global Research Bangalore,India

WAVELET DIFFERENCE REDUCTION WITH REGION-OF-INTEREST PRIORITY IN MULTISPECTRALVIDEO - SMALL TARGET DETECTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1903Yee Law, University of California, San Diego, USA; Frank Crosby, Quyen Huynh, Naval Surface Warfare Center,Dahlgren Division, USA; and Truong Nguyen, University of California, San Diego, USA

TOWARDS A NEW DIAGNOSIS AID OF CARDIOVASCULAR DISEASES USING 2D-MULTIMODALDATA REGISTRATION AND 3D-DATA SUPERIMPOSITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1907Gaelle Valet, Stephane Sanchez, Juan Manuel Lopez-Hernandez, Christian Daul, Didier Wolf, CRAN - INPL -ENSEM, France; and Gilles Karcher, CHU Nancy, France

TOWARDS A FRACTIONED TREATMENT IN CONFORMAL RADIOTHERAPY USING 3D-MULTIMODAL DATA REGISTRATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1911Ruben Posada, Christian Daul, Didier Wolf, CRAN-ENSEM-INPL, France; Pierre Aletti, Centre Alexis Vautrin,France; and Rosebet Miranda, CRAN-ENSEM-INPL, France

SUB-PIXEL REGISTRATION AND ESTIMATION OF LOCAL SHIFTS DIRECTLY IN THE FOURIERDOMAIN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1915Hassan Foroosh and Murat Balci, University of Central Florida, USA

FAST ALIGNMENT OF DIGITAL IMAGES USING A LOWER BOUND ON AN ENTROPY METRIC. . . . . . . 1919Mert Sabuncu and Peter Ramadge, Princeton University, USA

INTEGRATED REGISTRATION OF DYNAMIC RENAL PERFUSION MR IMAGES . . . . . . . . . . . . . . . . . . . . . . . 1923Ying Sun, Carnegie Mellon University, USA; Marie-Pierre Jolly, Siemens Corporate Research, USA; and Jose’Moura, Carnegie Mellon University, USA

SESSION TP-P1: Stereoscopic and 3-D Processing II

3D ORTHOGRAPHIC RECONSTRUCTION BASED ON ROBUST FACTORIZATION METHOD WITHOUTLIERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1927Li Xi, Institute of Artificial Intelligence and Robotics, Xian Jiaotong University, Xian, Shaanxi Province 710049,PR China, China

SURFACE SEGMENTATION USING A MODIFIED BALL-PIVOTING ALGORITHM . . . . . . . . . . . . . . . . . . . . . . 1931Andres Restrepo Specht and Michel Devy, LAAS-CNRS, France

A GENERAL FRAMEWORK FOR 3D SOCCER BALL ESTIMATION AND TRACKING . . . . . . . . . . . . . . . . . . . 1935Jinchang Ren, James Orwell, Graeme Jones and Ming Xu, Digital Imaging Research Centre, Kingston University,UK

MULTISCALE SURFACE REPRESENTATION AND RENDERING FOR POINT CLOUDS . . . . . . . . . . . . . . . . . 1939Sung-Bum Park, Sang-Uk Lee, Seoul National University, South Korea; and Hyeokho Choi, Rice University, USA

AREA MATCHING BASED ON BELIEF PROPAGATION WITH APPLICATIONS TO FACE MODELING . . . 1943Davide Onofrio, Augusto Sarti and Stefano Tubaro, Politecnico di Milano, Italy

OPTIMIZED SPACE SAMPLING FOR CIRCULAR IMAGE CUBE TRAJECTORY ANALYSIS . . . . . . . . . . . . . 1947Ingo Feldmann, Peter Kauff and Peter Eisert, Fraunhofer Institute for Telecommunications, Heinrich-Hertz-Institute, Germany

PERFORMANCE ANALYSIS OF AN IMPROVED TENSOR BASED CORRESPONDENCE ALGORITHMFOR AUTOMATIC 3D MODELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1951Ajmal Mian, Mohammed Bennamoun and Robyn Owens, The University of Western Australia, Australia

A STRUCTURE-FROM-MOTION METHOD FOR 3-D RECONSTRUCTION OF MOVING OBJECTS FROMMULTIPLE-VIEW IMAGE SEQUENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1955Ha Le, Department of Electrical and Computer Engineering, Vietnam National University, Hanoi, Vietnam

A FACTORIZATION-BASED PROJECTIVE RECONSTRUCTION ALGORITHM WITH CIRCULARMOTION CONSTRAINT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1959Yan Li, Wai-Kai Tang and Yeung-Sum Hung, Department of Electrical and Electronic Engineering, The Universityof Hong Kong, Hong Kong

3D GAIT ESTIMATION FROM MONOSCOPIC VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1963Angel D. Sappa, CVC, Spain; Niki Aifanti, Sotiris Malassiotis and Michael G. Strintzis, ITI, Greece

MULTI-RESOLUTION STREAMING AND RENDERING OF 3-D DYNAMIC DATA . . . . . . . . . . . . . . . . . . . . . . . 1967Ramanathan Subramanian, Ashraf Kassim, National University of Singapore, Singapore; Sumit Gupta, IndianInstitute of Technology, Roorkee, India; and Kuntal Sengupta, National University of Singapore, Singapore

MULTI-RESOLUTION SURFACE RECONSTRUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1971Mingyi He, Bangshu Xiong and Huajing Yu, Northwestern Polytechnical University, China

PROGRESSIVE COMPRESSION OF 3D DYNAMIC MESH SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1975Jeong-Hyu Yang, Seoul Nat’l Univ., South Korea; Chang-Su Kim, The Chinese Univ. of Hong Kong, Hong Kong;and Sang-Uk Lee, Seoul Nat’l Univ., South Korea

IMAGE FUSION AND WAVELET ANALYSIS FOR 3-D RECONSTRUCTION USING 2-D IMAGESOBTAINED UNDER DIFFERENT ILLUMINATION CONDITIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1979Thomas Heger, Madhukar Pandit and Robert Meisner, University of Kaiserslautern, Germany

SESSION TP-P2: Face Detection, Recognition and Classification III

IMPROVING INDOOR AND OUTDOOR FACE RECOGNITION USING UNIFIED SUBSPACE ANALYSISAND GABOR FEATURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1983Xiaogang Wang and Xiaoou Tang, The Chinese University of Hong Kong, Hong Kong

A FACE IMAGE RECOGNITION SCHEME WITH STRONG TOLERANCES TO LIGHTINGFLUCTUATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1987Kenji Matsuo, Masayuki Hashimoto and Atsushi Koike, KDDI R&D Laboratories Inc., Japan

SEPARATING USEFUL FROM USELESS IMAGE VARIATION FOR FACE RECOGNITION . . . . . . . . . . . . . . . 1991Peter Kalocsai, UCLA, USA

ROBUST NOSE DETECTION IN 3D FACIAL DATA USING LOCAL CHARACTERISTICS . . . . . . . . . . . . . . . . 1995Chenghua Xu, Yunhong Wang, Tieniu Tan, National Lab of Pattern Recognition, China; and Long Quan, Depart-ment of Computer Science, HKUST, China

FACIAL SIMILARITY ACROSS AGE,DISGUISE, ILLUMINATION AND POSE . . . . . . . . . . . . . . . . . . . . . . . . . . . 1999Narayanan Ramanathan, Electrical & Computer Engineering, USA; Amit Chowdhury, University of California,Riverside, USA; and Rama Chellappa, Centre for Automation Research, USA

3D FACE RECOGNITION USING LOCAL SHAPE MAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2003Yueming Wang, Gang Pan and Zhaohui Wu, Zhejiang University, China

COLOR CHANNEL ENCODING WITH NMF FOR FACE RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2007Menaka Rajapakse, I2R, Singapore; and Jagath Rajapakse, NTU, Singapore

A NOVEL COMBINED FISHERFACES FRAMEWORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2011Wenshu Li, College of Computer Science and Technology, Zhejiang University, China; and Changle Zhou, Depart-ment of Artificial Intelligence,Xiamen University, China

FACE DETECTION IN THE COMPRESSED DOMAIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2015Pedro Fonseca, Instituto Superior Tecnico - Instituto de Telecomunicacoes, Portugal; and Jan Nesvadba, PhilipsResearch, The Netherlands

ONLINE FACE RECOGNITION SYSTEM FOR VIDEOS BASED ON MODIFIED PROBABILISTIC NEURALNETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2019Jun Fan, Nevenka Dimitrova, Philips Research USA, USA; and Vasanth Philomin, Philips Research Aachen, Ger-many

DISCRIMINATIVE LIP-MOTION FEATURES FOR BIOMETRIC SPEAKER IDENTIFICATION . . . . . . . . . . . . 2023H. Ertan Cetingul, Yucel Yemez, Engin Erzin and A. Murat Tekalp, Koc University, Turkey

FEATURE-BASED DETECTION OF FACES IN COLOR IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2027Huang Chi-Jaung, Ho Ming-Che and Chiang Cheng-Chin, National Dong Hwa University, China

PATTERN RECOGNITION IN COMPRESSED DCT DOMAIN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2031Daidi Zhong and Irek Defe, Tampere University of Technology, Finland

SESSION TP-P3: Video Streaming and Networking

OPTIMAL RETRANSMISSION TIMEOUT SELECTION FOR DELAY-CONSTRAINED MULTIMEDIACOMMUNICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2035Jianfei Cai, Wenning Zhan, Nanyang Technological University, Singapore; and Zhihai He, University of Missouri-Columbia, USA

PEER-TO-PEER MULTIPOINT VIDEOCONFERENCING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2039M. Reha Civanlar, Oznur Ozkasap and Tahir Celebi, Koc University, Turkey

OPTIMAL RATE AND INPUT FORMAT CONTROL FOR CONTENT AND CONTEXT ADAPTIVE VIDEOSTREAMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2043Tanir Ozcelebi, Murat Tekalp and Reha Civanlar, Koc University, Turkey

CROSS LAYER OPTIMIZATION FOR WIRELESS MULTI-USER VIDEO STREAMING . . . . . . . . . . . . . . . . . . . 2047Eckehard Steinbach, Lai-U Choi, Munich University of Technology, Germany; and Wolfgang Kellerer, DoCoMoCommunication Laboratories Europe GmbH, Germany

RATE-DISTORTION-COMPLEXITY ADAPTIVE VIDEO COMPRESSION AND STREAMING . . . . . . . . . . . . 2051Mihaela Van der Schaar, UC Davis, USA; Deepak Turaga, Sony Electronics, USA; and Venkatesh Akella, UCDavis, USA

LOW-COMPLEXITY RATE-DISTORTION OPTIMIZED VIDEO STREAMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2055Jacob Chakareski, Stanford University, USA; John Apostolopoulos, Hewlett-Packard Laboratories, USA; andBernd Girod, Stanford University, USA

EFFICIENT CONGESTION CONTROL FOR STREAMING SCALABLE VIDEO OVER UNRELIABLE IPNETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2059Patrick Ssesanga and Mrinal Mandal, University of Alberta, Canada

IMPROVED MACROBLOCK-BASED REVERSE PLAY ALGORITHM FOR MPEG VIDEO STREAMING . . 2063Chang-Hong Fu, Yui-Lam Chan and Wan-Chi Siu, The Hong Kong Polytechnic University, Hong Kong

A REGION BASED MULTIPLE FRAME-RATE TRADEOFF OF VIDEO STREAMING. . . . . . . . . . . . . . . . . . . . . 2067Wei Lai, University of Science and Technology of China, China; Xiaodong Gu, Microsoft Research Asia, China;RenHua Wang, LiRong Dai, University of Science and Technology of China, China; and Hongjiang Zhang, Mi-crosoft Research Asia, China

FLEXIBLE P-PICTURE (FLEXP) CODING FOR THE EFFICIENT FINE-GRAULAR SCALABILITY (FGS) . 2071You Zhou, University of Science & Technology of Beijing, China; Xiaoyan Sun, Feng Wu, Microsoft Research Asia,China; Hong Bao, University of Science & Technology of Beijing, China; and Shipeng Li, Microsoft ResearchAsia, China

INCREASING BANDWIDTH UTILIZATION IN NEXT GENERATION IPTV NETWORKS . . . . . . . . . . . . . . . . . 2075Ulf Jennehag and Tingting Zhang, Mid-Sweden University, Sweden

CHANNEL-AWARE RATE-DISTORTION OPTIMIZED LEAKY MOTION PREDICTION . . . . . . . . . . . . . . . . . . 2079Zhen Li and Edward Delp, School of Electrical and Computer Engineering, Purdue University, West Lafayette,USA

DISTORTION-BUFFER OPTIMIZED TCP VIDEO STREAMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2083Anshul Sehgal, University of Illinois, Urbana, USA; Olivier Verscheure, IBM T. J. Watson Research, USA; andPascal Frossard, EPFL, Switzerland, Switzerland

OPTIMAL PER-PIXEL ESTIMATION FOR SCALABLE VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2087Athanasios Leontaris and Pamela C. Cosman, University of California, San Diego, USA

SESSION TP-P4: Shape Extraction and Analysis

COMPLEX CURVE TRACING BASED ON A MINIMUM SPANNING TREE MODEL AND REGULARIZEDFUZZY CLUSTERING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2091Lam Shu Yan and Yan Hong, Department of Computer Engineering and Information Technology, Hong Kong

SHAPE CLASSIFICATION OF PARTIALLY OCCLUDED OBJECTS USING SUBSPACE DETECTORS . . . . . 2095Arnt B. Salberg, Alf Harbitz, Institute of Marine Research, Dept. Tromsø, Norway; and Alfred Hanssen, Univsersityof Tromsø, Dept. Physics, Norway

THREE-DIMENSIONAL INTRINSIC SHAPE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2099Victor Ha, Samsung Information Systems America, USA; and Jose Moura, Carnegie Mellon University, USA

A ROBUST SHAPE-FROM-SHADING USING MULTIPLE SURFACE NORMAL APPROXIMATIONS . . . . . . 2103Osamu Ikeda, Takushoku University, Japan

SURFACE HEIGHT RECOVERY FROM SURFACE NORMALS USING MANIFOLD EMBEDDING . . . . . . . . 2107Antonio Robles-Kelly and Edwin Hancock, The University of York, UK

ROBUST CIRCLE DETECTION USING A WEIGHTED MSE ESTIMATOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2111Guido Schuster, Hochschule Rapperswil, Switzerland; and Aggelos Katsaggelos, Northwestern University, USA

REDUCED CROSS-DISCRIMINATION FOR DISCRIMINATIVE FILTERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2115Alexandre Mendonca, Instituto Militar de Engenharia - DE/3, Brazil; and Eduardo Da Silva, Universidade Federaldo Rio de Janeiro - Programa de Engenharia Eletrica/COPPE, Brazil

EXTRACTING PROJECTIVE INVARIANT OF 3D LINE SET FROM A SINGLE VIEW . . . . . . . . . . . . . . . . . . . . 2119Zhe Chen, School of Computer Science,Northwestern Polytechnical University, China

A NEW REPRESENTATION OF CHARACTER SHAPE AND ITS USE IN ON-LINE CHARACTERRECOGNITION BY A SELF ORGANIZING MAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2123Neila Mezghani, Amar Mitiche, INRS-EMT, Canada; and Mohamed Cheriet, ETS, Canada

CONSTRUCTING THE TOPOLOGICAL SOLUTION OF JIGSAW PUZZLES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2127Johan De Bock, Patrick De Smet, Wilfried Philips and Johan D’Haeyer, Ghent University, Dep. TELIN, Belgium

BLURRED IMAGE RECOGNITION BASED ON COMPLEX MOMENT INVARIANTS . . . . . . . . . . . . . . . . . . . . 2131Zhang Tianxu and Liu Jin, HuaZhong University of Science and technology, China

NEW FEATURES FOR AFFINE-INVARIANT SHAPE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2135Carlos Ramon Pantaleon Dionisio and Hae Yong Kim, Universidade de Sao Paulo, Escola Politecnica, Brazil

WAVELET APPROXIMATION-BASED AFFINE INVARIANT 2-D SHAPE MATCHING ANDCLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2139Ibrahim El Rube’, Mohamed Kamel, University of Waterloo, Canada; and Maher Ahmed, Wilfrid Laurier Univer-sity, Canada

SESSION TP-P5: Watermarking IV

DIGITAL WATERMARKING BASED ON LOCALLY LINEAR EMBEDDING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2143Yonggang Fu, Ruimin Shen and Liping Shen, Shanghai Jiaotong University, China

APPLICATION OF BPCS STEGANOGRAPHY TO WAVELET COMPRESSED VIDEO. . . . . . . . . . . . . . . . . . . . . 2147Hideki Noda, Tomonori Furuta, Michiharu Niimi and Eiji Kawaguchi, Kyushu Institute of Technology, Japan

REDUNDANT IMAGE REPRESENTATIONS IN SECURITY APPLICATIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2151Philippe Jost, Pierre Vandergheynst and Pascal Frossard, Swiss Federal Institute of Technology, Switzerland

A STUDY ON A WATERMARKING METHOD FOR BOTH COPYRIGHT PROTECTION AND TAMPERDETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2155Jun Watanabe, Madoka Hasegawa and Shigeo Kato, Faculty of Engineering, Utsunomiya University, Japan

BLIND MPEG-2 VIDEO WATERMARKING ROBUST AGAINST SCALING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2159Yulin Wang and Alan Pearmain, Queen Mary College,University of London, UK

MULTIPLE-DESCRIPTION CODING FOR ROBUST IMAGE WATERMARKING. . . . . . . . . . . . . . . . . . . . . . . . . . 2163Ying-Fen Hsia, Chen-Yao Chang and Jay-Ray Liao, Department of Electrical Engineering, National Chung HsingUniversity, Taichung, Taiwan

SHORT N-SECURE FINGERPRINTING CODE FOR IMAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2167Won-gyum Kim, ETRI, South Korea; and Youngho Suh, ETRI/Digital Contents Research Division, South Korea

NEW REAL-TIME WATERMARKING ALGORITHM FOR COMPRESSED VIDEO IN VLC DOMAIN . . . . . . 2171Hefei Ling, Zhengding Lu and Fuhao Zou, School of Computer Science,Huazhong University of Sci-ence&Technology (HUST), China

ROTATION AND CROPPING RESILIENT DATA HIDING WITH ZERNIKE MOMENTS . . . . . . . . . . . . . . . . . . . 2175Palak K. Amin and Koddavayur P. Subbalakshmi, Stevens Institute of Technology, USA

NON-UNIFORM QUANTIZER DESIGN FOR IMAGE DATA HIDING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2179Ning Liu and K.P. Subbalakshmi, Stevens Institute of Technology, USA

COPYRIGHT TRACING USING INVARIANTS OF CONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2183Jinhui Chao, Shintaro Suzuki and Jongdae Kim, Chuo University, Japan

OPTIMAL WATERMARK DETECTION ON INTERPOLATED IMAGES UNDER NOISE. . . . . . . . . . . . . . . . . . . 2187Alexia Giannoula, Nikolaos V. Boulgouris and Dimitrios Hatzinakos, University of Toronto, Canada

WATERMARKING COLOR HISTOGRAMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2191Sujoy Roy and Ee-Chien Chang, NUS, Singapore

DH-LZW: LOSSLESS DATA HIDING IN LZW COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2195Hiuk Jae Shim, Jinhaeng Ahn and Byeungwoo Jeon, Sungkyunkwan University, Korea

SESSION TP-P6: Image/video Storage and Retrieval

TOWARD AN IMPROVED ERROR METRIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2199Qi Tian, Qing Xue, Jie Yu, University of Texas at San Antonio, USA; Nicu Sebe, University of Amsterdam, TheNetherlands; and Thomas S. Huang, University of Illinois at Urbana-Champaign, USA

RELATING WORDS AND IMAGE SEGMENTS ON MULTIPLE LAYERS FOR EFFECTIVE BROWSINGAND RETRIEVAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2203Andrea Kutics, Tokyo University of Technology / NTT Data Corporation, Japan; Akihiko Nakagawa, NTT DataCorporation, Japan; Shoji Arai, Japan Systems Co., Ltd., Japan; Hiroyuki Tanaka and Sakuichi Ohtsuka, NTTData Corporation, Japan

MULTI-LABEL SVM ACTIVE LEARNING FOR IMAGE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2207Xuchun Li, Lei Wang and Eric Sung, Nanyang Technological University, Singapore

GENERALIZATION OF THE ANGULAR RADIAL TRANSFORM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2211Julien Ricard, David Coeurjolly and Atilla Baskurt, LIRIS, France

MULTI-LAYER SEMANTIC REPRESENTATION LEARNING FOR IMAGE RETRIEVAL . . . . . . . . . . . . . . . . . . 2215Wei Jiang, Guihua Er and Qionghai Dai, Department of Automation, Tsinghua University, China

RETIN AL: AN ACTIVE LEARNING STRATEGY FOR IMAGE CATEGORY RETRIEVAL . . . . . . . . . . . . . . . . . 2219Philippe-H Gosselin and Matthieu Cord, ETIS CNRS UMR 8051, France

ACTION SEGMENTATION AND RECOGNITION IN MEETING ROOM SCENARIOS . . . . . . . . . . . . . . . . . . . . . 2223Frank Wallhoff, Martin Zobl and Gerhard Rigoll, Technical University of Munich, Germany

SHARING VIDEO ANNOTATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2227Yaron Caspi, The Hebrew University of Jerusalem, Israel; and David Bargeron, Microsoft Research, USA

COMBINING LUMINANCE AND EDGE BASED METRICS FOR ROBUST TEMPORAL VIDEOSEGMENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2231Edmundo Saez, Jose Benavides, University of Cordoba, Spain; and Nicolas Guil, University of Malaga, Spain

A NOVEL COMPRESSED DOMAIN SHOT SEGMENTATION ALGORITHM ON H.264/AVC . . . . . . . . . . . . . . 2235Yang Liu, Wei Zeng, Harbin Institute of Technology, China; Weiqiang Wang, Graduate College, Chinese Academyof Science, China; and Wen Gao, Harbin Institute of Technology, China

A NOVEL HASHING ALGORITHM FOR VIDEO SEQUENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2239Antonio Mucedero, Rosa Lancini and Francesco Mapelli, CEFRIEL - Politecnico di Milano, Italy

TRAJECTORY-BASED VIDEO RETRIEVAL BY STRING MATCHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2243JunWei Hsieh, Shang-Li Yu and Yung-Sheng Chen, Department of Electrical Engineering, Yuan Ze University,Taiwan

NEWS SPORTS VIDEO SHOT CLASSIFICATION WITH SPORTS PLAY FIELD AND MOTION FEATURES 2247De-Hong Wang, Qi Tian, Sheng Gao, Institute for Infocomm Research, Singapore; and Wing-Kin Sung, NationalUniversity of Singapore, Singapore

SESSION TP-P7: Wavelet Video Coding and Scalability II

ADAPTIVE LOSSLESS VIDEO COMPRESSION USING AN INTEGER WAVELET TRANSFORM . . . . . . . . . 2251Sahng-Gyu Park, Edward Delp, School of Electrical and Computer Engineering, Purdue University, USA; andHaoping Yu, Thomson Corporation, Indianapolis, IN, USA

A MODEL-BASED MOTION COMPENSATED VIDEO CODER WITH JPEG2000 COMPATIBILITY . . . . . . . 2255Marco Cagnazzo, Thomas Andre, Marc Antonini and Michel Barlaud, I3S Laboratory, UMR 6070 of CNRS, Uni-versity of Nice-Sophia Antipolis, France

DRIFT REDUCTION FOR A H.264/AVC FINE GRAIN SCALABILITY WITH MOTION COMPENSATIONARCHITECTURE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2259Joao Ascenso, Escola Superior de Tecnologia de Setubal, Instituto das Telecomunicacoes, Portugal; and FernandoPereira, Instituto Superior Tecnico, Instituto das Telecomunicacoes, Portugal

MULTIPLE DESCRIPTION WAVELET CODING OF LAYERED VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2263Nikolaos Boulgouris, University of Toronto, Canada; Konstantinos Zachariadis, Northwestern Univerity, USA;Angelos Kanlis and Michael Strintzis, Informatics and Telematics Institute, Greece

ENERGY DISTRIBUTED UPDATE STEPS(EDU) IN LIFTING BASED MOTION COMPENSATED VIDEOCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2267Bo Feng, Tsinghua University, China; Jizheng Xu, Feng Wu, Microsoft Research Asia, China; Shiqiang Yang,Tsinghua University, China; and Shipeng Li, Microsoft Research Asia, China

LAYERED MOTION ESTIMATION AND CODING FOR FULLY SCALABLE 3D WAVELET VIDEOCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2271Ruiqin Xiong, Institute of Computing Technology, Chinese Academy of Sciences, China; Jizheng Xu, Feng Wu,Shipeng Li, Microsoft Research Asia, China; and Ya-Qin Zhang, Microsoft, USA

ENHANCED MOTION ESTIMATION FOR INTERFRAME WAVELET VIDEO CODING. . . . . . . . . . . . . . . . . . . 2275Chia-Yang Tsai, Han-Kuang Hsu, Hsiang-Cheh Huang, Hsueh-Ming Hang, National Chiao Tung University, Tai-wan; and Guo-Zua Wu, Industrial Technology Research Institute, Taiwan

PERFECT RECONSTRUCTION DEINTERLACER BANKS FOR FIELD SCALABLE VIDEOCOMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2279Shogo Muramatsu, Takuma Ishida and Hisakazu Kikuchi, Niigata University, Japan

MOTION COMPENSATED TEMPORAL FILTERING WITH OPTIMAL TEMPORAL DISTANCE BETWEENEACH MOTION COMPENSATION PAIR. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2283Yang Liu, Nanyang Technological Univerisyt, Singapore; Zhengguo Li, Institute for Infocomm Research, Singa-pore; and Yeng Chai Soh, Nanyang Technological University, Singapore

FAST IN-BAND MOTION ESTIMATION WITH VARIABLE SIZE BLOCK MATCHING . . . . . . . . . . . . . . . . . . . 2287Marco Tagliasacchi, Stefano Tubaro, Augusto Sarti and Davide Maestroni, Dipartimento di Elettronica e Infor-mazione - Politecnico di Milano, Italy

MOTION-COMPENSATED TEMPORAL FILTERING WITHIN THE H.264/AVC STANDARD . . . . . . . . . . . . . . 2291Emrah Akyol, Murat Tekalp and Reha Civanlar, KOC University, Turkey

OPTIMUM BIT ALLOCATION FOR FGS VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2295Jun Xie, Liang-Tien Chia and Bu-Sung Lee, School of Computer Engineering, Nanyang Technological University,Singapore

SIMPLE AVC-BASED CODECS WITH SPATIAL SCALABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2299Rafa Lange, Lukasz Baszak and Marek Domanski, Poznan University of Technology, Poland

MOTION WAVELET DIFFERENCE REDUCTION (MWDR) VIDEO CODEC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2303Yee Law and Truong Nguyen, University of California, San Diego, USA

SESSION TP-P8: Image Modeling

THE SALIENCY GROUPING FIELD. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2307Maurizio Pilu, HP Labs, UK

GLOBAL MODULATORY FACTORS IN DCT-BASED JUST-NOTICEABLE-DISTORTION ESTIMATION . . 2311Zhongkang Lu, W. S. Lin, X. K. Yang, E. P. Ong and Susu Yao, Institute for Infocomm research, Singapore

PERCEPTUAL MODEL BASED DATA EMBEDDING IN MEDICAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2315Samarendra Dandapat, Opas Chutatape and Shankar M. Krishnan, EEE, NTU, Singapore

UTILISING OBJECTIVE PERCEPTUAL IMAGE QUALITY METRICS FOR IMPLICIT LINK ADAPTATION 2319Tubagus Maulana Kusuma, Manora Caldera and Hans-Jurgen Zepernick, WATRI, Australia

SCALE-BASED FORMULATIONS OF STATISTICAL SELF-SIMILARITY IN IMAGES. . . . . . . . . . . . . . . . . . . . 2323Seungsin Lee and Raghuveer Rao, Rochester Institute of Technology, USA

PERFORMANCE ASSESSMENT OF A VISUAL ATTENTION SYSTEM ENTIRELY BASED ON A HUMANVISION MODELING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2327Olivier Le Meur, Thomson, France; Patrick Le Callet, Dominique Barba, IRCCyN, France; and DominiqueThoreau, Thomson, France

COLOR IMAGE COMPRESSION USING ADAPTIVE COLOR QUANTIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . 2331Chun-Hsien Chou and Kuo-Cheng Liu, Department of Electrical Engineering, Tatung University, Taiwan

TEXTURE CHARACTERIZATION AND COMPRESSION BASED ON HUMAN PERCEPTION IN THEJPEG2000 FRAMEWORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2335Gamal Fahmy, West Virginia University, USA; John Black and Sethuraman Panchanathan, Arizona State Univer-sity, USA

ESTIMATION OF THE RADIOMETRIC RESPONSE FUNCTIONS OF A COLOR CAMERA FROMDIFFERENTLY ILLUMINATED IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2339Khurram Shafique and Mubarak Shah, University of Central Florida, USA

IMPROVE ROBUSTNESS OF IMAGE WATERMARKING VIA ADAPTIVE RECEIVING . . . . . . . . . . . . . . . . . . 2343Xiangui Kang, Jiwu Huang, Sun Yat-Sen University, China; and Yun Q. Shi, New Jersey Institute of Technology,USA

AN EFFICIENT MOTION DETECTION ALGORITHM BASED ON A STATISTICAL NON PARAMETRICNOISE MODEL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2347Alessandro Bevilacqua, Luigi Di Stefano and Alessandro Lanza, DEIS-ARCES(Centre of Excellence), Universityof Bologna, Italy

LEARNING STRUCTURED DICTIONARIES FOR IMAGE REPRESENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 2351Gianluca Monaci and Pierre Vandergheynst, Signal Processing Institute (ITS) - EPFL, Switzerland

IMAGE UNDERSTANDING AND SCENE MODELS: A GENERIC FRAMEWORK INTEGRATING DOMAINKNOWLEDGE AND GESTALT THEORY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2355Nicolas Zlatoff, Bruno Tellez and Atilla Baskurt, LIRIS, France

STOCHASTIC MODELING OF VOLUME IMAGES WITH A 3-D HIDDEN MARKOV MODEL . . . . . . . . . . . . 2359Jia Li, Dhiraj Joshi and James Wang, Pennsylvania State University, USA

Table of Contents

Volume III

Wednesday, October27th, 2004

SESSION WA-S1: Content Understanding for Home Photograph andVideo Management

AUTOMATED RED-EYE DETECTION AND CORRECTION IN DIGITAL PHOTOGRAPHS . . . . . . . . . . . . . . . 2363Lei Zhang, Yanfeng Sun, Mingjing Li and Hongjiang Zhang, Microsoft Research Asia, China

IMPROVED BLUE SKY DETECTION USING POLYNOMIAL MODEL FIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2367Andrew Gallagher, Jiebo Luo and Wei Hao, Eastman Kodak Company, USA

UNIFYING LOCAL AND GLOBAL CONTENT-BASED SIMILARITIES FOR HOME PHOTO RETRIEVAL . 2371Joo-Hwee Lim, Institute for Infocomm Research, Singapore; and Jesse Jin, University of New South Wales, Aus-tralia

OVER-COMPLETE REPRESENTATION AND FUSION FOR SEMANTIC CONCEPT DETECTION. . . . . . . . . 2375Apostol Natsev, Milind Naphade, Ching-Yung Lin and John R. Smith, IBM T J Watson Research, USA

SESSION WA-S2: Pattern Discovery in Real-world Broadcast Video

VIDEO MINING: PATTERN DISCOVERY VS PATTERN RECOGNITION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2379Ajay Divakaran, Kadir Peker, Mitsubishi Electric Research Laboratories, USA; Shih-Fu Chang, Columbia Uni-versity, USA; Regunathan Radhakrishnan, Mitsubishi Electric Research Laboratories, USA; and Lexing Xie,Columbia University, USA

DISCOVERING MEANINGFUL MULTIMEDIA PATTERNS WITH AUDIO-VISUAL CONCEPTS ANDASSOCIATED TEXT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2383Lexing Xie, Lyndon Kennedy, Shih-Fu Chang, Dept. of Electrical Engineerng, Columbia University, USA; AjayDivakaran, Huifang Sun, MERL, USA; and Ching-Yung Lin, IBM Research, USA

A COMPARISON OF CONTINUOUS VS. DISCRETE IMAGE MODELS FOR PROBABILISTIC IMAGE ANDVIDEO RETRIEVAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2387Arjen De Vries and Thijs Westerveld, Centrum voor Wiskunde en Informatica (CWI), The Netherlands

MULTIMODAL INFORMATION FUSION FOR VIDEO CONCEPT DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . 2391Yi Wu, ECE Dept, University of California Santa Barbara, USA; Ching-Yung Lin, IBM T.J. Watson ResearchCenter, Hawthorne, USA; Edward Y. Chang, ECE Dept, University of California Santa Barbara, USA; and JohnR. Smith, IBM T.J. Watson Research Center, Hawthorne, USA

SESSION WA-L1: Image Scanning, Display, and Printing I

EFFICIENT CLASSIFICATION OF SCANNED MEDIA USING SPATIAL STATISTICS . . . . . . . . . . . . . . . . . . . . 2395Gozde Unal, Siemens Corporate Research, USA; Gaurav Sharma, University of Rochester, USA; and Reiner Es-chbach, Xerox Corporation, USA

EFFICIENT INSCRIBING OF NOISY RECTANGULAR OBJECTS IN SCANNED IMAGES . . . . . . . . . . . . . . . . 2399Cormac Herley, Microsoft, USA

NON-PHOTOREALISTIC RENDERING FROM MULTIPLE IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2403Alberto Bartesaghi, Guillermo Sapiro, University of Minnesota, USA; Tom Malzbender and Dan Gelb, Hewlett-Packard Laboratories, USA

A SMALL-SIZE CHINESE FONT DISPLAY BY PERCEPTION-BASED METHOD . . . . . . . . . . . . . . . . . . . . . . . . 2407Thou-Ho (Chao-Ho) Chen, Yung-Chuen Chiou, Department of Electronic Engineering, National Kaohsiung Uni-versity of Applied Sciences, Taiwan; and Chao-Tan Huang, Department of Electrical Engineering, National Tai-wan University, Taiwan

RECOVERING IMAGING DEVICE SENSITIVITIES: A DATA-DRIVEN APPROACH . . . . . . . . . . . . . . . . . . . . . . 2411Paulo Carvalho, Amancio Santos and Pedro Martins, CISUC, Portugal

A CLASSIFICATION APPROACH TO COLOR DEMOSAICKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2415Cindy Kwan and Xiaolin Wu, McMaster University, Canada

ILLUMINATION ESTIMATION BASED ON VALID PIXEL SELECTION IN HIGHLIGHT REGION . . . . . . . . 2419Oh-Seol Kwon, Yang-Ho Cho, Yun-Tae Kim and Yeong-Ho Ha, School of Electrical Engineering and ComputerScience, Kyungpook National University, South Korea

DETECTION AND DETERRENCE OF COUNTERFEITING OF VALUABLE DOCUMENTS . . . . . . . . . . . . . . . 2423Cormac Herley, Microsoft, USA; Poorvi Vora, GWU, USA; and Shawn Yang, Cisco, USA

SESSION WA-L2: Image Formation I

AN EFFICIENT PHASE RETRIEVAL METHOD USING SNAKES FOR IMAGE RECONSTRUCTION . . . . . . 2427Keiko Kondo, Miki Haseyama and Hideo Kitajima, School of Engineering, Hokkaido University, Japan

FMRI SIGNAL MODELING USING LAGUERRE POLYNOMIALS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2431Victor Solo, EECS Department, University of Michigan, Ann Arbor, USA; Christopher Long, Martinos NMR Cen-ter, Mass. General Hospital, USA; Emery.N. Brown, Neuroscience Statistics Research Lab, Department of Anes-thesia and Critical Care, Mass. General Hospital, USA; Elissa Aminoff, Moshe Bar, Martinos NMR Center, Mass.General Hospital, USA; and Supratim Saha, cience Statistics Research Lab, Department of Anesthesia and CriticalCare, Mass. General Hospital, USA

SIMPLIFIED DIGITAL HOLOGRAPHIC RECONSTRUCTION USING STATISTICAL METHODS. . . . . . . . . . 2435Jeffrey A. Fessler, University of Michigan, USA; and Saowapak Sotthivirat, National Electronics and ComputersTechnology Center, Thailand

A SET THEORETIC APPROACH TO TARGET DETECTION USING SPECTRAL SIGNATURE STATISTICS 2439David Rouse and Joel Trussell, NC State University, USA

KNOWLEDGE-DRIVEN SEGMENTATION OF THE CENTRAL SULCUS FROM HUMAN BRAIN MRIMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2443Wei Zuo, Qingmao Hu, Aamer Aziz, Biomedical Imaging Group, BII, Singapore; Kiafock Loe, School of Comput-ing, NUS, Singapore; and Wieslaw Nowinski, Biomedical Imaging Group, BII, Singapore

A FEASIBILITY STUDY ON A NOVEL METHOD OF VISUAL OBSTACLE DETECTION . . . . . . . . . . . . . . . . . 2447Andrzej Sluzek, Nanyang Technological University, School of Computer Engineering, Singapore; and Ching SeongTan, Nanyang Technological University, School of Mechanical & Production Engineering, Singapore

A PRACTICAL ALGORITHM TO CORRECT GEOMETRICAL DISTORTION OF IMAGE ACQUISITIONCAMERAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2451Juan Torres and Jose Manuel Menendez, Universidad Politecnica de Madrid, Espana

HIGH SPEED PROCESSING OF BIOMEDICAL IMAGES USING PROGRAMMABLE GPU. . . . . . . . . . . . . . . . 2455Jin Young Hong, Human Computer Interaction Master Program, USA; and May D. Wang, The Wallace H. CoulterDepartment of Biomedical Engineering, Georgia Institute of Technology and Emory University, USA

SESSION WA-L3: Stereoscopic and 3-D Coding & Processing

REGION-ORIENTED COMPRESSION OF MULTISPECTRAL IMAGES BY SHAPE-ADAPTIVE WAVELETTRANSFORM AND SPIHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2459Marco Cagnazzo, Giovanni Poggi, Luisa Verdoliva, Universita Federico II di Napoli, Italy; and Andrea Zinicola,LABCOM - CNIT, Italy

RATE-DISTORTION ANALYSIS OF RANDOM ACCESS FOR COMPRESSED LIGHT FIELDS . . . . . . . . . . . . 2463Prashant Ramanathan and Bernd Girod, Stanford University, USA

MULTI-VIDEO COMPRESSION IN TEXTURE SPACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2467Gernot Ziegler, Hendrik P.A. Lensch, Naveed Ahmed, Marcus Magnor and Hans-Peter Seidel, MPI Informatik,Saarbrucken, Germany

VIEW-DEPENDENT NON-UNIFORM SAMPLING FOR IMAGE-BASED RENDERING . . . . . . . . . . . . . . . . . . . 2471Cha Zhang and Tsuhan Chen, ECE, Carnegie Mellon Univ., USA

A FOCUS MEASURE FOR LIGHT FIELD RENDERING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2475Keita Takahashi, The University of Tokyo, Japan; Akira Kubota, Carnegie Mellon University, USA; and TakeshiNaemura, The University of Tokyo, Japan

COMPLETE 3-D MODELS FROM VIDEO: A GLOBAL APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2479Bruno B. Goncalves and Pedro M. Q. Aguiar, ISR/IST, Portugal

ROBUST EGO-MOTION ESTIMATION AND 3D MODEL REFINEMENT USING DEPTH BASEDPARALLAX MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2483Amit Agrawal and Rama Chellappa, CFAR, UMD, USA

VARIOUS IMAGE TAKING STRATEGIES FOR 3-D OBJECT MODELING BASED ON MULTIPLECAMERAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2487Joo Kooi Tan, Iku Yamaguchi, Seiji Ishikawa, Kyushu Institute of Technology, Japan; Shunji Hirokawa, KyushuUniversity, Japan; and Tomonori Tabusa, Yuge National College of Technology, Japan

SESSION WA-L4: Image Coding I

ROBUST WIRELESS TRANSMISSION OF REGIONS OF INTEREST IN JPEG2000 . . . . . . . . . . . . . . . . . . . . . . . 2491Victor Sanchez, Mrinal Mandal, Dept. of EE; Univ. of Alberta, Canada; and Anup Basu, Dept. of CS; Univ. ofAlberta, Canada

BASIS PICKING FOR MATCHING PURSUITS IMAGE CODING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2495Don Monro, University of Bath, UK

MINIMUM HARDWARE IMPLEMENTATION OF MULTIPLIERS OF THE LIFTING WAVELETTRANSFORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2499Yoshihide Tonomura, Nagaoka University of Technology, Japan; Somchart Chokchaitam, Thammasat University,Thailand; and Masahiro Iwahashi, Nagaoka University of Technology, Japan

A WAVELET-BASED TWO-STAGE NEAR-LOSSLESS CODER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2503Sehoon Yea and William Pearlman, Rensselaer Polytechnic Institute, USA

THEORETICAL ANALYSIS ON OPTIMUM WORD LENGTH ASSIGNMENT FOR INTEGER DCT . . . . . . . . 2507Masahiro Iwahashi, Kohtaro Nakagawa, Nagaoka University of Technology, Japan; Somchart Chokchaitam,Thammasat University, Thailand; and Yoshihide Tonomura, Nagaoka University of Technology, Japan

DESIGN OF IIR ORTHOGONAL WAVELET FILTER BANKS USING LIFTING SCHEME. . . . . . . . . . . . . . . . . . 2511Xi Zhang, University of Electro-Communications, Department of Information and Communication Engineering,Japan; Wei Wang, Toshinori Yoshikawa and Yoshinori Takei, Nagaoka University of Technology, Japan

ROTATION OF FOVEATED IMAGE IN THE WAVELET DOMAIN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2515Hang Yu, Vu-Thanh Nguyen and Ee-Chien Chang, School of Computing, National University of Singapore, Singa-pore

LOW COMPLEXITY LOSSLESS VIDEO COMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2519Yao-Chun Fang, Chun-Yi Lee, Yin-Ming Wang, Chung-Neng Wang and Tihao Chiang, National Chiao Tung Uni-versity, Taiwan

SESSION WA-L5: Source-Channel Coding I

WIRELESS TRANSMISSION OF IMAGES USING JPEG2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2523Nikolaos Thomos, Informatics and Telematics Institute, Greece; Nikolaos Boulgouris, Univeristy of Toronto,Canada; and Michael Strintzis, University of Thessaloniki, Greece

ENCODER AND DECODER OPTIMIZATION FOR SOURCE-CHANNEL PREDICTION IN ERRORRESILIENT VIDEO TRANSMISSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2527Hua Yang and Kenneth Rose, Electrical and Computer Engineering Department, University of California SantaBarbara, USA

AN INTEGRATED JOINT SOURCE-CHANNEL CODING FRAMEWORK FOR VIDEO TRANSMISSIONOVER PACKET LOSSY NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2531Fan Zhai, Yiftach Eisenberg, Thrasyvoulos Pappas, Randall Berry and Aggelos Katsaggelos, Northwestern Uni-versity, USA

LAYERED UNEQUAL LOSS PROTECTION WITH PRE-INTERLEAVING FOR PROGRESSIVE IMAGETRANSMISSION OVER PACKET LOSS CHANNELS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2535Jianfei Cai, Xiangjun Li, Nanyang Technological University, Singapore; and Chang Wen Chen, Florida Instituteof Technology, USA

RATE-CONSTRAINED ADAPTIVE FEC FOR VIDEO OVER ERASURE CHANNELS WITH MEMORY . . . . 2539Shirish Karande and Hayder Radha, Michigan State University, USA

JOINT OBJECT-BASED VIDEO ENCODING AND POWER MANAGEMENT FOR ENERGY EFFICIENTWIRELESS VIDEO COMMUNICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2543Haohong Wang, Yiftach Eisenberg, Fan Zhai and Aggelos Katsaggelos, Northwestern University, USA

CONGESTION-AWARE RATE ALLOCATION FOR MULTIPATH VIDEO STREAMING OVER AD HOCWIRELESS NETWORKS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2547Xiaoqing Zhu, Sangeun Han and Bernd Girod, Stanford University, USA

ERROR RESILIENT MQ CODER AND MAP JPEG 2000 DECODING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2551Marco Grangetto, Enrico Magli and Gabriella Olmo, Politecnico di Torino, Italy

SESSION WA-P1: Motion Detection and Estimation: Optical Flow andChange Detection

DENSE MOTION FIELD ESTIMATION BY 3-D GABOR REPRESENTATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2555Mu Feng and Todd Reed, University of Hawaii at Manoa, USA

ESTIMATE LARGE MOTIONS USING RELIABILITY-BASED DYNAMIC PROGRAMMING . . . . . . . . . . . . . . 2559Minglun Gong, Laurentian Univ., Canada; and Yee-Hong Yang, Univ. of Alberta, Canada

AUDIO-VISUAL FLOW - A VARIATIONAL APPROACH TO MULTI-MODAL FLOW ESTIMATION . . . . . . . 2563Raffay Hamid, Aaron Bobick, GVU - College of Computing - Georgia Institute of Technology, USA; and AnthonyYezzi, School of Electrical and Computer Engineering - Georgia Institute of Technology, USA

BENEFITS OF TEMPORAL OVERSAMPLING IN OPTICAL FLOW ESTIMATION. . . . . . . . . . . . . . . . . . . . . . . . 2567SukHwan Lim, John Apostolopoulos, Hewlett-Packard Laboratories, USA; and Abbas El Gamal, Stanford Univer-sity, USA

ATLAS-BASED MOTION CORRECTION FOR ON-LINE MR TEMPERATURE MAPPING. . . . . . . . . . . . . . . . . 2571Denis De Senneville Baudouin, IMF, ERT CNRS, France; Quesson Bruno, Image Guided Therapy, France; Des-barats Pascal, LaBRI, UMR 5800 CNRS, France; Salomir Rares, U386 INSERM, France; Palussiere Jean, InstitutBergonie, France; and C.T.W. Moonen, IMF, ERT CNRS, France

SHAPE PRIOR BASED SEGMENTATION FOR ORGAN DEFORMATION CORRECTION . . . . . . . . . . . . . . . . . 2575Jun Xie, H.T. Tsui, Electronic Engineering Department, The Chinese University of Hong Kong, Hong Kong; andLam Wai-Man, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong

TRACKING DEFORMABLE OBJECTS IN GEOSPATIAL APPLICATIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2579Sotirios Gyftakis, Peggy Agouris and Anthony Stefanidis, University of Maine, USA

A MOTION CONFIDENCE MEASURE FROM PHASE INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2583Long To, Mark Pickering, Michael Frater and John Arnold, University College, The University of New SouthWales, Australia

A NEW FEATURE CLUSTERING METHOD FOR OBJECT DETECTION WITH AN ACTIVE CAMERA . . . 2587Christian Micheloni, Gian Luca Foresti and Flavio Alberti, Department of Computer Science, University of Udine,Italy

UNSUPERVISED MOTION DETECTION USING A MARKOVIAN TEMPORAL MODEL WITH GLOBALSPATIAL CONSTRAINTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2591Pierre-Marc Jodoin and Max Mignotte, University of Montreal, Canada

DETECTION AND TRACKING OF MOVING OBJECTS IN IMAGE SEQUENCES. . . . . . . . . . . . . . . . . . . . . . . . . 2595Min Xu, Ruixin Niu and Pramod Varshney, Dept. of EECS, Syracuse University, USA

MOTION DETECTION BASED ON CONTOUR STRINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2599Michael Kellner and Tobias Hanning, FORWISS, University of Passau, Germany

POSE ESTIMATION USING FEATURE CORRESPONDENCES AND DTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2603Ronen Lerner, Ehud Rivlin, The Technion, Dept. of Computer Science, Israel; and P.Hector Rotstein, University ofMinnesota, Dept. of Aerospace Engineering and Mechanics, Minnesota

MARKERLESS MOTION CAPTURE WITH SINGLE AND MULTIPLE CAMERAS. . . . . . . . . . . . . . . . . . . . . . . . 2607Paris Kaimakis and Joan Lasenby, Cambridge University Engineering Department, UK

SESSION WA-P2: Watermarking V

ROTATION AND SCALE INSENSITIVE IMAGE WATERMARKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2611Maxime Ossonce, Claude Delpha and Pierre Duhamel, LSS, France

A PRACTICAL VERSION OF WONG’S WATERMARKING TECHNIQUE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2615Abdelkader Ouda and Mahmoud El-Sakka, University of Western Ontario, Canada

IMPROVED BIT RATE CONTROL FOR COMPRESSED VIDEO WATERMARKING. . . . . . . . . . . . . . . . . . . . . . . 2619Sugiri Pranata, Viktor Wahadaniah, Yong Liang Guan and Hock Chuan Chua, Nanyang Technological University,Singapore

MODEL BASED STEGANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2625Xiaoyi Yu, Yunhong Wang and Tieniu Tan, National Laboratory of Pattern Recognition, Institute of Automation,Chinese Academy of Science, China

AN IMAGE-QUALITY GUARANTEED METHOD FOR QUANTIZATION-BASED WATERMARKINGUSING A DWT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2629Masaaki Fujiyoshi and Hitoshi Kiya, Tokyo Metropolitan University, Japan

A BLIND CDMA IMAGE WATERMARKING SCHEME IN WAVELET DOMAIN . . . . . . . . . . . . . . . . . . . . . . . . . . 2633Santi P. Maity, B.E.College (D.U), Howrah, India; and Malay K. Kundu, Indian Statistical Institute, India

AUTHENTICATION OF LOSSY COMPRESSED VIDEO DATA BY SEMI-FRAGILE WATERMARKING. . . . 2637Tsong-Yi Chen, Chien-Hua Hunang, Thou-Ho Chen, Department of Electronic Engineering, National KaohsiungUniversity of Applied Sciences, Taiwan; and Cheng-Chieh Liu, Huper Laboratories Co., LTD, Taiwan

WATERMARKING FOR JPEG IMAGE AUTHENTICATION SURVIVING INTEGER ROUNDING INDECOMPRESSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2641Hiroshi Ito, Koichi Magai, Ryousuke Fujii and Mitsuyoshi Suzuki, Mitsubishi Electric Corporation, Japan

A CLASSIFIER DESIGN FOR DETECTING IMAGE MANIPULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2645Ismail Avcibas, Sevinc Bayram, Uludag University, Turkey; Nasir Memon, Polytechnic University, USA; and BulentSankur, Bogazichi University, Turkey

A NOVEL DIGITAL IMAGE WATERMARKING SCHEME USING BLIND SOURCE SEPARATION . . . . . . . . 2649Thang V. Nguyen, Jagdish C. Patra and Narendra S. Chaudhari, Nanyang Technological University, Singapore

A TRACEABLE CONTENT-ADAPTIVE FINGERPRINTING FOR MULTIMEDIA . . . . . . . . . . . . . . . . . . . . . . . . . 2653Yu-Tzu Lin and Ja-Ling Wu, CML, Dept. of CSIE, NTU, Taiwan

TRANSPARENT INFORMATION HIDING WITH AUTOMATIC EMBEDDING RANGE SELECTION FOROWNERSHIP VERIFICATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2657Farook Sattar, Dan Yu, Sirajudeen Gulam Razul and Shankar M. Krishnan, Nanyang Technological University,Singapore

HIERARCHICAL MULTIPLE IMAGE WATERMARKING FOR IMAGE AUTHENTICATION ANDOWNERSHIP VERIFICATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2661Jagdish C. Patra, Kah K. Ang and Ee-Luang Ang, Nanyang Technological University, Singapore

SESSION WA-P3: Feature Extraction and Analysis I

ESTIMATION OF MULTIPLE ORIENTATIONS IN MULTI-DIMENSIONAL SIGNALS . . . . . . . . . . . . . . . . . . . . 2665Cicero Mota, University of Luebeck, Germany; Til Aach, University of luebeck, Germany; Ingo Stuke and ErhardtBarth, University of Luebeck, Germany

CORNER DETECTION OF GRAY LEVEL IMAGES USING GABOR WAVELETS . . . . . . . . . . . . . . . . . . . . . . . . . 2669Xinting Gao, Farook Sattar, School of EEE, NTU, Singapore; and Ronda Venkateswarlu, Institute for InfocommResearch, Singapore

A FAST METHOD TO IMPROVE THE STABILITY OF INTEREST POINT DETECTION UNDERILLUMINATION CHANGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2673Flore Faille, Technische Universitaet Muenchen, Germany

THE ITERATIVE OBJECT SYMMETRY TRANSFORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2677Bertrand Zavidovique, IEF, University Paris XI, France; and Vito Di Gesu’, DMA, Universita’ di Palermo, Italy

FEATURE SPACE ANALYSIS USING LOW-ORDER TENSOR VOTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2681Jia Wang, Hanqing Lu and Qingshan Liu, National Laboratory of Pattern Recognition, Institute of Automa-tion,Chinese Academy of Sciences, China

EDGE AND LINE DETECTION AS EXERCISES IN HYPOTHESIS TESTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2685Garry Newsam, Defence Science & Technology Organisation, Australia

SURFACE RADIANCE: EMPIRICAL DATA AGAINST MODEL PREDICTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . 2689Hossein Ragheb and Edwin Hancock, Department of Computer Science, University of York, UK

OPTIMAL SEGMENTATION OF SIGNALS AND ITS APPLICATION TO IMAGE DENOISING ANDBOUNDARY FEATURE EXTRACTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2693Tony Han, University of Illinois, USA; Steven Kay, University of Rhode Island, USA; and Thomas Huang, Univer-sity of Illinois, USA

KERNEL GENERALIZED NONLINEAR DISCRIMINANT ANALYSIS ALGORITHM FOR PATTERNRECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2697Guang Dai and Yuntao Qian, College of Computer Science, Zhejiang University, China

SOURCE SEPARATION IN NOISY ASTROPHYSICAL IMAGES MODELLED BY MARKOV RANDOMFIELDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2701Ercan Kuruoglu, Anna Tonazzini and Laura Bianchi, ISTI-CNR, Italy

WATER VIDEO ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2705Lisa Spencer and Mubarak Shah, University of Central Florida, USA

FACE RECOGNITION USING REINFORCEMENT LEARNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2709Mehrtash Tafazzoli Harandi, Majid Nili Ahmadabadi and Babak N. Araabi, University of Tehran, Iran

A PROBABILISTIC FRAMEWORK FOR OBJECT RECOGNITION IN VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2713Omar Javed, Mubarak Shah, University of Central Florida, USA; and Dorin Comaniciu, Siemens CorporateResearch, USA

SESSION WA-P4: Image Segmentation: Level Set and Active Contour

SAR IMAGE SEGMENTATION WITH ACTIVE CONTOURS AND LEVEL SETS. . . . . . . . . . . . . . . . . . . . . . . . . . 2717Ismail Ben Ayed, Carlos Vazquez, Amar Mitiche, INRS-EMT, Canada; and Ziad Belhadj, Ecole Superieure desCommunications, Tunisia

IMAGE PARTIONING BY LEVEL SET MULTIREGION COMPETITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2721Abdol-Reza Mansouri, Amar Mitiche and Carlos Vazquez, INRS-EMT, Canada

INTERACTIVE SEGMENTATION USING CURVE EVOLUTION AND RELEVANCE FEEDBACK . . . . . . . . . 2725Motaz El Saban and Banglore Manjunath, UCSB, USA

SHAPE GRADIENT FOR MULTI-MODAL IMAGE SEGMENTATION USING MUTUAL INFORMATION . . 2729Ariane Herbulot, I3S Laboratory, France; Stephanie Jehan-Besson, GREYC-images Laboratory, France; MichelBarlaud, I3S Laboratory, France; and Gilles Aubert, Dieudonne Laboratory, France

MEDICAL IMAGE SEGMENTATION WITH MINIMAL PATH DEFORMABLE MODELS. . . . . . . . . . . . . . . . . . 2733Pingkun Yan and Ashraf Kassim, National University of Singapore, Singapore

AUTOMATED CELL NUCLEUS SEGMENTATION USING IMPROVED SNAKE . . . . . . . . . . . . . . . . . . . . . . . . . . 2737Min Hu, Xijian Ping and Yihong Ding, Information Engineering University, China

SEGMENTATION OF ANATOMICAL STRUCTURES FROM 3D BRAIN MRI USING AUTOMATICALLY-BUILT STATISTICAL SHAPE MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2741Jonathan Bailleul, Su Ruan, Daniel Bloyet and Barbara Romaniuk, GREYC - CNRS UMR 6072, France

CARTILAGE SURFACE TRACKING USING DIRECTIONAL GRADIENT VECTOR FLOW SNAKES . . . . . . 2745Jinshan Tang, Department of Electrical Engineering,University of Virginia, USA; Steven Millington, Center forApplied Biomechanics, Department of Orthopaedic Surgery,University of Virginia, USA; and Scott T Acton, De-partment of Electrical Engineering,University of Virginia, USA

CONVERGENCE ANALYSIS OF ACTIVE CONTOURS IN IMAGE SEGMENTATION. . . . . . . . . . . . . . . . . . . . . 2749Rafael Verdu Monedero, Juan Morales Sanchez, Ricardo Gonzalez Leon, Universidad Politecnica de Cartagena,Spain; and Luis Weruaga Prieto, Austrian Academy of Sciences, Austria

REMESHING ALGORITHM FOR MULTIRESOLUTION PRIOR MODEL IN SEGMENTATION . . . . . . . . . . . . 2753Gouaillard Alexandre, Gelas Arnaud, creatis, France; Valette Sebastien, LIS, France; Boix Eric, creatis, France;Kanai Takashi, Keio University, Japan; and Prost Remy, creatis, France

UNSUPERVISED SEGMENTATION ALGORITHM OF HRTEM IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2757Ainhoa Mendizabal, Julian Cabrera, Luis Salgado, Narciso Garcia and Juan Gonzalez, Universidad Politecnicade Madrid, Spain

SESSION WA-P5: Transcoding

A COMPRESSED-DOMAIN HETEROGENEOUS VIDEO TRANSCODER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2761Wan-Chi Siu, Kai-Tat Fung and Yui-Lam Chan, Hong Kong Polytechnic University, Hong Kong

AN IMPROVED RATE-QUANTIZATION MODEL FOR RATE CONTROL IN REAL-TIME VIDEOENCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2765Bo Xie, PacketVideo Corporation, USA; and Wenjun Zeng, Univ. of Missouri-Columbia, USA

I/P/B FRAME TYPE DECISION BY COLLINEARITY OF DISPLACEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2769Adriana Dumitras and Barry G. Haskell, Apple Computer, USA

RATE ESTIMATION FOR H.264/AVC SPATIAL RESOLUTION REDUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2773Peter H. W. Wong, Robert T. W. Hung, Jack Y. B. Lee, S. C. Liew, C. S. Kim, The Chinese University of Hong Kong,Hong Kong; and Roland T. Chin, The Hong Kong University of Science and Technology, Hong Kong

MPEG-21 DIGITAL ITEM ADAPTATION BY APPLYING PERCEIVED MOTION ENERGY TO H.264 VIDEO 2777Zhao Gang, Department of Electronics & Information Engineering,Huazhong University of Science & Technol-ogy, China; Liang-Tien Chia, Center for Multimedia and Network Technology,School of Computer Engineering,Nanyang Technological University, Singapore; and Yang Zongkai, Department of Electronics & Information En-gineering,Huazhong University of Science & Technology, China

MODE MAPPING METHOD FOR H.264/AVC SPATIAL DOWN-SCALING TRANSCODING . . . . . . . . . . . . . . 2781Peng Zhang, Institute of Computing Technology, Chinese Academy of Science, China; Yan Lu, Microsoft ResearchAsia, China; Qingming Huang and Wen Gao, Institute of Computing Technology, Chinese Academy of Science,China

FAST TRANSCODING OF INTRA FRAMES BETWEEN H.263 AND H.264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2785Jens Bialkowski, Andre Kaup, University of Erlangen-Nuremberg, Germany; and Klaus Illgner, Siemens AG,Germany

JOINT CONTROL FOR HYBRID TRANSCODING USING MULTIDIMENSIONAL RATE DISTORTIONMODELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2789Yong Ju Jung and Yong Man Ro, Information and Communications University, South Korea

FORMAT-INDEPENDENT SCALABLE BIT-STREAM ADAPTATION USING MPEG-21 DIA . . . . . . . . . . . . . . 2793Debargha Mukherjee, Geraldine Kuo, Shih-ta Hsiang, Sam Liu and Amir Said, Hewlett Packard Laboratories,USA

ON RESIZING IMAGES IN THE DCT DOMAIN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2797Carlos Salazar and Trac Tran, The Johns Hopkins University, USA

RESIZING OF IMAGES IN THE DCT SPACE BY ARBITRARY FACTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2801Jayanta Mukhopadhyay, Indian Institute of Technology, Kharagpur, India; and Sanjit Mitra, Univ. of California,Santa Barbara, USA

GRAPHICS-TO-VIDEO ENCODING FOR 3G MOBILE GAME VIEWER MULTICAST USING DEPTHVALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2805Gene Cheung, Takashi Sakamoto and Wai-tian Tan, Hewlett-Packard Laboratories, USA

INTEGRATED COMPRESSED DOMAIN RESOLUTION CONVERSION WITH DE-INTERLACING FOR DVTO MPEG-4 TRANSCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2809Haruhisa Kato, KDDI R&D Laboratories Inc., Japan; Takashi Sano, Tokyo University of Science, Japan; andYasuyuki Nakajima, KDDI R&D Laboratories Inc., Japan

SESSION WA-P6: Implementations and Systems

ARCHITECTURE OF MPEG-7 COLOR STRUCTURE DESCRIPTION GENERATOR FOR REALTIMEVIDEO APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2813Jing-Ying Chang, Graduate Institute of Electronics Engineering, National Taiwan University, Taiwan; Yen-WeiHuang, National Taiwan University, Taiwan; Liang-Gee Chen and Hung-Chi Fang, Graduate Institute of Elec-tronics Engineering, National Taiwan University, Taiwan

IMPROVED THROUGHPUT ARITHMETIC CODER FOR JPEG2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2817Michael Dyer, David Taubman and Saeid Nooshabadi, University of New South Wales, Australia

DESIGN FLEXIBILITY USING FPGA DYNAMICAL RECONFIGURATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2821Nicolas Abel, Lounis Kessal and Didier Demigny, ETIS - UMR 8051 CNRS, France

DESIGN AND FPGA IMPLEMENTATION OF NON-SEPARABLE 2-D BIORTHOGONAL WAVELETTRANSFORMS FOR IMAGE/VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2825Isa Servan Uzun and Abbes Amira, The Queen’s University of Belfast, UK

AUTOMATIC KEYSTONE CORRECTION FOR SMART PROJECTORS WITH EMBEDDED CAMERA . . . . 2829Baoxin Li and M. Ibrahim Sezan, Sharp Labs of America, USA

HIGH-THROUGHPUT IMAGE ROTATION USING SIGN-PREDICTION BASED REDUNDANT CORDICALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2833Suchitra Sathyanarayana, Siew Kei Lam and Srikanthan Thambipillai, Nanyang Technological University, Singa-pore

SMART IMAGE SENSOR FOR HIGH SPEED IN-FOCUS DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2837Takashi Yoshida, Arimitsu Yokota, Hideki Kashiyama and Takayuki Hamamoto, Tokyo University of Science, Japan

IMPLEMENTATION OF JPEG2000 ARITHMETIC DECODER USING DYNAMIC RECONFIGURATION OFFPGA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2841Sophie Bouchoux, Elbay Bourennane and Michel Paindavoine, LE2I, France

SCALABLE VIDEO CODING BASED ON MOTION-COMPENSATED TEMPORAL FILTERING:COMPLEXITY AND FUNCTIONALITY ANALYSIS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2845Fabio Verdicchio, Yiannis Andreopoulos, Tom Clerckx, Joeri Barbarien, Adrian Munteanu, Jan Cornelis and PeterSchelkens, Vrije Universiteit Brussel - ETRO, Belgium

A SMART CAMERA FOR FACE RECOGNITION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2849Richard Kleihorst, Philips Research Labs, The Netherlands; Martijn Reuvers, Ben Krose, University of Amsterdam,The Netherlands; and Harry Broers, Philips CFT, The Netherlands

OBJECT COLOR PROPAGATION IN AN UNREGISTERED DISTRIBUTED VIDEO SENSOR NETWORK. . 2853Vijay Venkataraman, Sabeshan Srinivasan and Anthony Stefanidis, University of Maine, USA

ACCELERATING THE COMPUTATION OF GLCM AND HARALICK TEXTURE FEATURES ONRECONFIGURABLE HARDWARE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2857Muhammad Atif Tahir, Ahmed Bouridane, Fatih Kurugollu and Abbes Amira, Queens University Belfast, UK

RATE AND DECODING POWER CONSTRAINED VIDEO CODING SCHEME FOR MOBILE MULTIMEDIAPLAYERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2861Ligang Lu and Vadim Sheinin, IBM Watson Research Center, USA

REALITY WINDOW MANAGER: A USER INTERFACE FOR MEDIATED REALITY . . . . . . . . . . . . . . . . . . . . . 2865Rosco Hill, James Fung and Steve Mann, University of Toronto, Canada

SESSION WA-P7: Document Image Processing and Other Applications

EFFICIENT AND RELIABLE DYNAMIC QUALITY CONTROL FOR COMPRESSION OF COMPOUNDDOCUMENT IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2869Amir Said, Hewlett Packard Laboratories, USA

CONTEXTUAL DISAMBIGUATION FOR MULTI-CLASS OBJECT DETECTION . . . . . . . . . . . . . . . . . . . . . . . . . 2873Xiaodong Fan, Dept. of Electrical and Computer Engineering, The Johns Hopkins University, USA

DOCUMENT IMAGE RECTIFICATION USING FUZZY SETS AND MORPHOLOGICAL OPERATORS . . . . 2877Shijian Lu, Ben M. Chen and C. C. Ko, National University of Singapore, Singapore

ON-LINE HANDWRITTEN CHINESE CHARACTER RECOGNITION USING A RADICAL-BASED AFFINETRANSFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2881Yuan-Bi Lai, Leu-Shing Lan, Ming-Yen Tsai and Chien-Chung Chiu, National Yunlin Univ. of Science and Tech.,Taiwan

VISUAL ECHO CANCELLATION IN A PROJECTOR-CAMERA-WHITEBOARD SYSTEM . . . . . . . . . . . . . . . . 2885Hanning Zhou, University of Illinois at Urbana-Champaign, USA; Zhengyou Zhang, Microsoft Research, USA;and Thomas Huang, University of Illinois at Urbana-Champaign, U.S

ELLIPTIC ARC VECTORIZATION FOR 3D PIE CHART RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2889Weihua Huang, Chew Lim Tan and Wee Kheng Leow, SOC, National University of Singapore, Singapore

DOCUMENT IMAGE SECRET SHARING USING BIT-LEVEL PROCESSING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2893Rastislav Lukac and Konstantinos Plataniotis, University of Toronto, Canada

ADAPTIVE PHOTO COLLECTION PAGE LAYOUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2897Clayton Atkins, Hewlett-Packard Labs, USA

A HIDDEN MARKOV MODEL FRAMEWORK FOR TRAFFIC EVENT DETECTION USING VIDEOFEATURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2901Xiaokun Li, University of Cincinnati, USA; and Fatih M. Porikli, Misubishi Electric Research Labs, USA

AUTOMATIC TEXT SEGMENTATION FROM COMPLEX BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2905Qixiang Ye, Institute of Computing Technology, China; Wen Gao and Qingming Huang, Graduate School of Chi-nese Academy of Sciences, China

TRACKING FOOTBALL PLAYERS WITH MULTIPLE CAMERAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2909Ming Xu, James Orwell and Graeme A. Jones, Kingston University, UK

IMAGE CONTENT-BASED ACTIVE SENSOR PLANNING FOR A MOBILE TRINOCULAR ACTIVEVISION SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2913Alaa E. Abdel-Hakim and Aly A. Farag, University of Louisville, USA

IDENTIFICATION OF INSECT DAMAGED WHEAT KERNELS USING TRANSMITTANCE IMAGES . . . . . 2917Zehra Cataltepe, Siemens Corporate Research, USA; Enis Cetin, Bilkent University, Turkey; and Tom Pearson, USDept of Agriculture, USA

SESSION WA-P8: Biomedical Image Processing: Segmentation and Com-puter Assisted Screening & Diagnosis

DETECTION AND RECOGNITION OF LUNG NODULES IN SPIRAL CT IMAGES USING DEFORMABLETEMPLATES AND BAYESIAN POST-CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2921Aly Farag, Ayman El-Baz, CVIP lab, University of Louisville, USA; Georgy Gimel’ farb, University of Auckland,New Zealand; and Robert Falk, Jewish Hospital, USA

3D MEDICAL IMAGE SEGMENTATION APPROACH BASED ON MULTI-LABEL FRONT PROPAGATION 2925Hua Li, Greyc-Ensicaen, France; Abderrahim Elmoataz, LUSAC, Site Universitaire, France; Jalal Fadili, Greyc-Ensicaen, France; Su Ruan, Equipe Image, L.A.M., France; and Barbara Romaniuk, Greyc-Ensicaen, France

CHROMOSOME COUNTING VIA DIGITAL IMAGE ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2929Victor Gajendran and Jeffrey J. Rodriguez, University of Arizona, USA

QUANTITATIVE ANALYSIS OF LYMPHOCYTE MEMBRANE PROTEIN REDISTRIBUTION FROMFLUORESCENCE MICROSCOPY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2933Peter Kasson, Johannes Huppa, Mark Davis and Axel Brunger, Stanford University School of Medicine, USA

CELL NUCLEI SEGMENTATION USING FUZZY LOGIC ENGINE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2937Grigory Begelman, Computer Science Dept., Technion- Israel Institute of Technology, Israel; Eran Gur, Faculty ofEng., Tel-Aviv University, Israel; Ehud Rivlin, Michael Rudzsky, Computer Science Dept., Technion- Israel Instituteof Technology, Israel; and Zeev Zalevsky, School of Engineering, Bar-Ilan University, Israel

TEXTURE CLASSIFICATION OF SARS INFECTED REGION IN RADIOGRAPHIC IMAGE . . . . . . . . . . . . . . . 2941Xiaoou Tang, Dacheng Tao and Gregory E. Antonio, The Chinese University of Hong Kong, Hong Kong

BLOOD FLOW GENERATION IN B-MODE ULTRASOUND IMAGES OF THE CAROTID ARTERY . . . . . . . 2945Ali Hamou and Mahmoud El-Sakka, The University of Western Ontario, Canada

ESTIMATION OF MIXTURES OF PROBABILISTIC PCA WITH STOCHASTIC EM FOR THE 3DBIPLANAR RECONSTRUCTION OF SCOLIOTIC RIB CAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2949Said Benameur, Ecole de technologie Superieure, Canada; Max Mignotte, Francois Destrempes, Universite deMontreal, Canada; and Jacques De Guise, Ecole de technologie Superieure, Canada

MICROCALCIFICATION DETECTION BASED ON LOCALIZED TEXTURE COMPARISON . . . . . . . . . . . . . . 2953Xin Yuan and Pengcheng Shi, Hong Kong University of Science and Technology, Hong Kong

BREAST CANCER DIAGNOSIS USING IMAGE RETRIEVAL FOR DIFFERENT ULTRASONIC SYSTEMS 2957Yu-Len Huang, Department of Computer Science and Information Engineering Tunghai University, Taiwan; Dar-Ren Chen, Department of General Surgery China Medical College & Hospital, Taiwan; and Ya-Kuang Liu, De-partment of Computer Science and Information Engineering Tunghai University, Taiwan

GENDER DETERMINING METHOD USING THERMOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2961Satoshi Nishino, Sachiyo Igarashi and Atsushi Matsuda, Oyama National College of Technology, Japan

SESSION WP-L1: Image Representation, Rendering, and Quality Assess-ment

CAMERA RESPONSE FUNCTION RECOVERY FROM DIFFERENT ILLUMINATIONS OF IDENTICALSUBJECT MATTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2965Corey Manders, Chris Aimonie and Mann Steve, University of Toronto, Canada

CLUSTERING-BASED MATCH PROPAGATION FOR IMAGE-BASED RENDERING FROM MULTIPLEIMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2969Jian Yao and Wai-Kuen Cham, Department of Electronic Engineering, The Chinese University of Hong Kong,Hong Kong

A TRAINING-BASED NO-REFERENCE IMAGE QUALITY ASSESSMENT ALGORITHM . . . . . . . . . . . . . . . . 2973Huitao Luo, HP Labs, USA

A CALIBRATED PINHOLE CAMERA MODEL FOR SINGLE VIEWPOINT OMNIDIRECTIONALIMAGING SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2977Daniel Moldovan and Toshikazu Wada, Wakayama University, Japan

AUTOMATIC DETECTION OF DIGITAL ZOOMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2981Jerome Buzzi and Frederic Guichard, DO Labs, France

UNIQUENESS OF BLUR MEASURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2985Jerome Buzzi and Frederic Guichard, DO Labs, France

ARBITRARY VIEWPOINTS IMAGE REPRESENTATION BASED ON 3-D GEOMETRIC MODEL ANDSPECULAR REFLECTION TRACING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2989Masaaki Endo, Takahiro Matsushita, Koichi Fukuda and Akira Kawanaka, Sophia University, Japan

STEREOSCOPIC IMAGE GENERATION BASED ON DEPTH IMAGES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2993Liang Zhang, Wa James Tam and Demin Wang, Communications Research Centre Canada, Canada

SESSION WP-L2: Stereoscopic Image Processing and 3D Modeling

A LAYERED STEREO ALGORITHM USING IMAGE SEGMENTATION AND GLOBAL VISIBILITYCONSTRAINTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2997Michael Bleyer and Margrit Gelautz, Interactive Media Systems Group, Institute for Software Technology andInteractive Systems, Vienna University of Technology, Austria

AN ENERGY-BASED FRAMEWORK USING GLOBAL SPATIAL CONSTRAINTS FOR THE STEREOCORRESPONDENCE PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3001Pierre-Marc Jodoin and Max Mignotte, University of Montreal, Canada

STRUCTURED LIGHT SYSTEM CONFIGURATION DETERMINATION FOR EFFICIENT 3D SURFACERECONSTRUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3005Albert Dipanda and Sanghyuk Woo, Laboratoire LE2I, France

VIRTUAL VIEW SYNTHESIS THROUGH LINEAR PROCESSING WITHOUT GEOMETRY . . . . . . . . . . . . . . . 3009Akira Kubota, Kiyoharu Aizawa, Univ. of Tokyo, Japan; and Tsuhan Chen, Carnegie Mellon Univ., USA

OPTIMAL HIERARCHICAL REPRESENTATION AND SIMULATION OF CLOTH AND DEFORMABLEOBJECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3013Konstantinos Moustakas, Aristotle University of Thessaloniki, Electrical and Computer Engineering Dept.,Greece; Dimitrios Tzovaras, Informatics and Telematics Institute, Greece; and Michael G. Strintzis, AristotleUniversity of Thessaloniki, Electrical and Computer Engineering Dept., Greece

ROBUST RECONSTRUCTION OF 3D POINTS FROM IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3017Rui Rodrigues and Antonio Fernandes, Universidade do Minho, Portugal

3-D GEOMETRY ENHANCEMENT BY CONTOUR OPTIMIZATION IN TURNTABLE SEQUENCES . . . . . . 3021Peter Eisert, Fraunhofer Institute for Telecommunications, Heinrich-Hertz-Institute, Germany

IMPROVEMENT OF PHASE-BASED ALGORITHMS FOR DISPARITY ESTIMATION BY MEANS OFMAGNITUDE INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3025Udo Ahlvers and Udo Zoelzer, Helmut-Schmidt-University / University of the Federal Armed Forces, Departmentof Signal Processing and Communications, Germany

SESSION WP-L3: Feature Extraction and Analysis II

COLOR INVARIANT DENSITY ESTIMATION FOR IMAGE SEGMENTATION AND OBJECT TRACKING 3029Theo Gevers and Frank Aldershoff, University of Amsterdam, The Netherlands

COMPACT ROTATION-INVARIANT TEXTURE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3033Paul Southam and Richard Harvey, University of East Anglia, UK

OPTIMAL MULTIRESOLUTION POLYGONAL APPROXIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3037Alexander Kolesnikov and Pasi Franti, University of Joensuu, Finland

AFFINE-INVARIANT CURVE MATCHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3041Marco Zuliani, Sitaram Bhagavathy, Department of Electrical and Computer Engineering, University of Califor-nia, Santa Barbara, USA; B. S. Manjunath, Department of Electrical and Computer Engineering,University ofCalifornia, Santa Barbara, USA; and C. S. Kenney, Department of Electrical and Computer Engineering, Univer-sity of California, Santa Barbara, USA

MOVING SHADOW REPRESENTATION BASED ON A LEVEL CURVES DECOMPOSITION . . . . . . . . . . . . . 3045Henri Nicolas, INRIA, France

A NOVEL IMAGE RECOGNITION METHOD BASED ON FEATURE-EXTRACTION VECTOR SCHEME . . 3049Masao Hiramoto, Panasonic Information Systems Co.,Ltd, Japan; Takahiro Ogawa and Miki Haseyama, HokkaidoUniversity, Japan

FEATURE POINT EXTRACTION USING SCALE-SPACE REPRESENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3053Yousri Abdeljaoued and Touradj Ebrahimi, Swiss Federal Institute of Technology, Switzerland

QUATERNION WAVELETS FOR IMAGE ANALYSIS AND PROCESSING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3057Wai Lam Chan, Hyeokho Choi and Richard Baraniuk, Rice University, USA

SESSION WP-L4: Image/Video Segmentation and Tracking

BACKGROUND MODELING AND SUBTRACTION BY CODEBOOK CONSTRUCTION. . . . . . . . . . . . . . . . . . 3061Kyungnam Kim, Computer Vision Lab, University of Maryland, USA; Thanarat Chalidabhongse, Faculty of Infor-mation Technology, King Mongkut’s Institute of Technology, Thailand; David Harwood and Larry Davis, Com-puter Vision Lab, University of Maryland, USA

A DETECTION-BASED MULTIPLE OBJECT TRACKING METHOD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3065Mei Han, NEC Labs America, USA; Amit Sethi, UIUC, USA; Wei Hua and Yihong Gong, NEC Labs America, USA

RECOVERING FIELD OF VIEW LINES BY USING PROJECTIVE INVARIANTS . . . . . . . . . . . . . . . . . . . . . . . . . 3069Senem Velipasalar and Wayne Wolf, Princeton University, USA

OPTIMAL SENSOR SELECTION FOR VIDEO-BASED TARGET TRACKING IN A WIRELESS SENSORNETWORK. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3073Peshala Pahalawatta, Thrasyvoulos Pappas and Aggelos Katsaggelos, Northwestern University, USA

MORPHOLOGICAL SEGMENTATION PRODUCES A VORONOI TESSELATION OF THE MARKERS . . . . 3077Fernand Meyer, Ecole des Mines de Paris, France

GRAPH-BASED REPRESENTATION FOR 2-D SHAPE USING DECOMPOSITION SCHEME . . . . . . . . . . . . . . 3081Duck Hoon Kim, Seoul National University, Republic of Korea; Il Dong Yun, Hankuk University of Foreign Studies,Republic of Korea; and Sang Uk Lee, Seoul National University, Republic of Korea

PATH-BASED MORPHOLOGICAL OPENINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3085Henk Heijmans, CWI, The Netherlands; Michael Buckley and Hugues Talbot, CSIRO, Australia

MORPHOLOGICAL GRADIENT OPERATORS FOR COLOUR IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3089Adrian Evans, University of Bath, UK

SESSION WP-L5: Distributed Source Coding and Scalability

VIDEO MULTICAST OVER LOSSY CHANNELS BASED ON DISTRIBUTED SOURCE CODING . . . . . . . . . 3093Abhik Majumdar and Kannan Ramchandran, U.C. Berkeley, USA

WYNER-ZIV VIDEO CODING WITH HASH-BASED MOTION COMPENSATION AT THE RECEIVER . . . . 3097Anne Aaron, Shantanu Rane and Bernd Girod, Stanford University, USA

SYSTEMATIC LOSSY FORWARD ERROR PROTECTION FOR ERROR-RESILIENT DIGITAL VIDEOBROADCASTING - A WYNER-ZIV CODING APPROACH. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3101Shantanu Rane, Anne Aaron and Bernd Girod, Stanford University, USA

DISTRIBUTED CODING OF MULTISPECTRAL IMAGES: A SET THEORETIC APPROACH . . . . . . . . . . . . . . 3105Xin Li, LDCSEE, WVU, USA

ANALYSIS OF THE EFFICIENCY OF SNR-SCALABLE STRATEGIES FOR MOTION COMPENSATEDVIDEO CODERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3109Josep Prades-Nebot, Departamento de Comunicaciones. Universidad Politecnica de Valencia, Spain; GregoryCook, School of Medicine. Indiana University, USA; and Edward Delp, Video and Image Processing Laboratory.Purdue University, USA

SNR-SCALABLE EXTENSION OF H.264/AVC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3113Heiko Schwarz, Detlev Marpe and Thomas Wiegand, Fraunhofer Institute for Telecommunications - Heinrich HertzInstitute, Germany

UNIFORM MOTION-COMPENSATED 5/3 FILTERBANK FOR SUBBAND VIDEO CODING . . . . . . . . . . . . . . 3117Gregoire Pau and Beatrice Pesquet-Popescu, ENST, France

RATE-DISTORTION BOUNDS FOR MOTION COMPENSATED RATE SCALABLE VIDEO CODERS . . . . . . 3121Gregory W. Cook, Purdue University, USA; Josep Prades-Nebot, Universidad Politcnicia de Valencia, Spain; andEdward J. Delp, Purdue Univeristy, USA

SESSION WP-L6: Video Streaming

A HYBRID WAVELET FRAMEWORK FOR MODELING VBR VIDEO TRAFFIC . . . . . . . . . . . . . . . . . . . . . . . . . 3125Min Dai, Dmitri Loguinov, Texas A&M University, USA; and Hayder Radha, Michigan State University, USA

MULTIPLE DESCRIPTION CODING WITH ERROR CORRECTION CAPABILITIES: AN APPLICATION TOMOTION JPEG 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3129Tammam Tillo, Marco Grangetto and Gabriella Olmo, Politecnico di Torino, Italy

OVERLAY MULTI-HOP FEC SCHEME FOR VIDEO STREAMING OVER PEER-TO-PEER NETWORKS. . . 3133Yufeng Shan, Rensselaer Polytechnic Institute, USA; Ivan Bajic, University of Miami, USA; Shivkumar Kalyanara-man and John Woods, Rensselaer Polytechnic Institute, USA

EFFICIENT PATH AGGREGATION AND ERROR CONTROL FOR VIDEO STREAMING. . . . . . . . . . . . . . . . . . 3137Omesh Tickoo, Shivkumar Kalyanaraman and John Woods, Rensselaer Polytechnic Institute, USA

RATE-DISTORTION OPTIMIZED STREAMING FOR 3-D WAVELET VIDEO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3141Chuo-Ling Chang, Sangeun Han and Bernd Girod, Stanford University, USA

RATE-DISTORTION OPTIMIZED STREAMING OF VIDEO WITH MULTIPLE INDEPENDENTENCODINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3145Mark Kalman and Bernd Girod, Stanford University, USA

JOINT SERVER/PEER RECEIVER-DRIVEN RATE-DISTORTION OPTIMIZED VIDEO STREAMINGUSING ASYNCHRONOUS CLOCKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3149Danjue Li, Department of ECE, University of California, Davis, USA; Gene Cheung, HP Laboratories, Japan,Japan; Chen-Nee Chuah and S.J.Ben Yoo, Department of ECE, University of California, Davis, USA

MDC AND PATH DIVERSITY IN VIDEO STREAMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3153Siva Somasundaram, K.P. Subbalakshmi, Department of Electrical and Computer Engineering,Stevens Institute ofTechnology,, USA; and R.N. Uma, Department of Computer Science,University of Texas at Dallas,, USA

SESSION WP-P1: Image Coding II

IMAGE CODING WITH ITERATED CONTOURLET AND WAVELET TRANSFORMS . . . . . . . . . . . . . . . . . . . . 3157Vivien Chappelier, IRISA/Universite de Rennes 1, France; Christine Guillemot and Slavica Marinkovic, IRISA,France

FAST VQ ENCODING ALGORITHMS USING ANGULAR CONSTRAINT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3161Kousuke Imamura, Ahmed Swilem and Hideo Hashimoto, Kanazawa University, Japan

WAVELET IMAGE CODING BY DILATION-RUN ALGORITHM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3165Zheng Wu and Mingyi He, Northwestern Polytechnical University, China

AN IMPROVED EZW ALGORITHM BASED ON SET PARTITIONING IN HIERARCHICAL TREES USINGWAVELET REGULARITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3169Sergio Penedo and Rui Seara, Federal University of Santa Catarina, Brazil

CONCURRENT ENCODING IN HIERACHICAL TREES FOR WAVELET BASED IMAGE COMPRESSION 3173Jing-Xin Wang, Dept. of CSIE. National Cheng-Kung University, Tainan, Taiwan, Taiwan; Fang-Hsuan Cheng,Dept. of CSIE. Chung-Hwa University, HsinChu, Taiwan, Taiwan; and Alvin W.Y. Su, Dept. of CSIE. NationalCheng-Kung University, Tainan, Taiwan, Taiwan

IMPROVED FAST SEARCH METHOD FOR VECTOR QUANTIZATION USING DISCRETE WALSHTRANSFORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3177Zhibin Pan, Koji Kotani and Tadahiro Ohmi, Tohoku University, Japan

PRACTICAL LOW BIT RATE PREDICTIVE IMAGE CODER USING MULTI-RATE PROCESSING ANDADAPTIVE ENTROPY CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3181Anna N. Kim and Tor A. Ramstad, Norwegian University of Science and Technology, Norway

CT IMAGE COMPRESSION WITH LEVEL OF INTEREST. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3185Masayuki Hashimoto, Kenji Matsuo, Atsushi Koike, KDDI R&D Laboratories Inc., Japan; Hiroki Hayashi, Na-tional Institute of Information and Communications Technology, Japan; and Tetsuo Shimono, Hokkaido TokaiUniversity, Japan

WAVELET-BASED CONTOURLET TRANSFORM AND ITS APPLICATION TO IMAGE CODING . . . . . . . . . 3189Ramin Eslami and Hayder Radha, Michigan State University, USA

L∞ NORM BASED SECOND GENERATION IMAGE CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3193Marco Dalai and Riccardo Leonardi, Department of Electronics for Automation, University of Brescia, Italy

AN EFFECTIVE FRACTAL IMAGE CODING METHOD WITHOUT SEARCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3197Shen Furao and Osamu Hasegawa, Tokyo Institute of Technology, Japan

MULTIDIMENSIONAL SIGNAL COMPRESSION USING MULTI-SCALE RECURRENT PATTERNS WITHSMOOTH SIDE-MATCH CRITERION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3201Eddie Filho, Genius Institute of Technology, Brazil; Murilo De Carvalho, TEC/CTC Universidade Federal Flumi-nense, Brazil; and Eduardo Da Silva, Programa de Engenharia Eletrica/COPPE Universidade Federal do Rio deJaneiro, Brazil

COLOR AND R.O.I. WITH JPEG2000 FOR WIRELESS VIDEOSURVEILLANCE. . . . . . . . . . . . . . . . . . . . . . . . . . 3205Franck Luthon and Brice Beaumesnil, LIUPPA Laboratory, France

SESSION WP-P2: Source-channel Coding II

OPTIMIZATION OF H264 FOR LOW DELAY VIDEO COMMUNICATIONS OVER LOSSY CHANNELS . . . 3209Oztan Harmanci and Murat Tekalp, University of Rochester, USA

POLYPHASE SPATIAL SUBSAMPLING MULTIPLE DESCRIPTION CODING OF VIDEO STREAMS WITHH264 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3213Riccardo Bernardini, Marco Durigon, Roberto Rinaldo, University of Udine, Italy; Luca Celetto and Andrea Vitali,ST Microelectronics, Italy

SELECTIVE FEC FOR ERROR-RESILIENT IMAGE CODING AND TRANSMISSION USING SIMILARITYCHECK FUNCTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3217Tuyet-Trang Lam, Lina J. Karam, Rida A. Bazzi, Arizona State University, USA; and Glen P. Abousleman, GeneralDynamics C4 Systems, USA

ITERATIVE JOINT SOURCE-CHANNEL DECODING OF VARIABLE LENGTH ENCODED VIDEOSEQUENCES EXPLOITING SOURCE SEMANTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3221Hang Nguyen, Alcatel R&I, France; and Pierre Duhamel, CNRS/LSS-Supelec, France

A NOVEL VISUAL DISTORTION SENSITIVITY ANALYSIS FOR VIDEO ENCODER BIT ALLOCATION . 3225Chih-Wei Tang, Department of Electronics Engineering, National Chiao Tung University, Taiwan; Ching-Ho Chen,Ya-Hui Yu and Chun-Jen Tsai, Department of Computer Science and Information Engineering, National ChiaoTung University, Taiwan

A NEW MULTIPLE DESCRIPTION LAYERED CODING METHOD OVER AD-HOC NETWORK . . . . . . . . . . 3229Song Xiao, ISN National Key Lab., Xidian University, China; Chengke Wu, ISN National key lab., Xidian Univer-sity, China; and Fang Zhang, ISN National Key lab., Xidian University, China

A LOW-COMPLEXITY SOFT VLC DECODER USING PERFORMANCE MODELING . . . . . . . . . . . . . . . . . . . . 3233Tsu-Ming Liu and Chen-Yi Lee, Institute of Electronics Engineering, National Chiao Tung University, Taiwan

SLICE GROUP BASED MULTIPLE DESCRIPTION VIDEO CODING USING MOTION VECTORESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3237Dong Wang, Nishan Canagarajah and David Bull, University of Bristol, UK

A PARA-PSEUDO INVERSE BASED METHOD FOR RECONSTRUCTION OF FILTER BANKFRAME-EXPANDED SIGNALS FROM ERASURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3241Ravi Motwani, DSI, Singapore; and Christine Guillemot, IRISA, INRIA, France

OPTIMIZED FILTERING AND RECONSTRUCTION IN PREDICTIVE QUANTIZATION WITH LOSSES . . . 3245Alyson Fletcher, University of California, Berkeley, USA; Sundeep Rangan, Flarion Technologies, USA; VivekGoyal, MIT, USA; and Kannan Ramchandran, University of California, Berkeley, USA

A JOINT SOURCE-CHANNEL DISTORTION MODEL FOR JPEG COMPRESSED IMAGES . . . . . . . . . . . . . . . 3249Muhammad Sabir, Hamid Sheikh, Robert Heath and Alan Bovik, The University of Texas at Austin, USA

CHANNEL MODELING AND ITS EFFECT ON THE END-TO-END DISTORTION IN WIRELESS VIDEOCOMMUNICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3253Eren Soyak, Ingenient Technologies, USA; Yiftach Eisenberg, Fan Zhai, Randall Berry, Thrasyvoulos Pappas andAggelos Katsaggelos, Northwestern University, USA

OPTIMAL OBJECT-BASED VIDEO COMMUNICATIONS OVER DIFFERENTIATED SERVICESNETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3257Haohong Wang, Fan Zhai, Yiftach Eisenberg and Aggelos Katsaggelos, Northwestern University, USA

SESSION WP-P3: Stereoscopic and 3-D Coding

UNCONSTRAINED FREE-VIEWPOINT VIDEO CODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3261Edouard Lamboray, Michael Waschbusch, Stephan Wurmlin, Markus Gross, ETH Zurich, Switzerland; andHanspeter Pfister, MERL Research Lab, USA

AN EFFICIENT CODING FOR 3-D GEOMETRY DATA BASED ON SURFACE SIMPLIFICATION ANDWAVELET TRANSFORM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3265Hiroki Amada, Kenji Kasai, Yutaka Saito, Kouichi Fukuda and Akira Kawanaka, Sohia University, Japan

SHARING OF MOTION VECTORS IN 3D VIDEO CODING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3271Stefan Grewatsch and Erika Muller, University of Rostock, Institute of Communications Engineering, Germany

SEGMENTATION BASED DISPARITY ESTIMATION USING COLOR AND DEPTH INFORMATION . . . . . . 3275Sang Yoon Park, Sang Hwa Lee and Nam Ik Cho, Seoul National University, South Korea

TECHNIQUES FOR IMPROVING STEREO DEPTH MAPS OF FACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3279Jason Baker, Vinod Chandran and Sridha Sridharan, Queensland University of Technology, Australia

LOSSY-TO-LOSSLESS BLOCK-BASED COMPRESSION OF HYPERSPECTRAL VOLUMETRIC DATA . . . 3283Xiaoli Tang and William Pearlman, Rensselaer Polytechnic Institute, USA

FREE VIEWPOINT VIDEO EXTRACTION, REPRESENTATION, CODING, AND RENDERING . . . . . . . . . . . 3287Aljoscha Smolic, Karsten Mueller, Philipp Merkle, Tobias Rein, Peter Eisert, Thomas Wiegand and MatthiasKautzner, Fraunhofer HHI, Germany

SESSION WP-P4: Super-resolution and Mosaic

RESTORATION AND DEMOSAICING FOR PIXEL MIXTURE IMAGES IN DSC VIDEO CLIPS . . . . . . . . . . . 3291Ikuko Tsubaki and Kiyoharu Aizawa, University of Tokyo, Japan

SINGLE-FRAME TEXT SUPER-RESOLUTION: A BAYESIAN APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3295Gerald Dalley, Mitsubishi Electric Research Labs, USA; Bill Freeman, Massachusetts Institute of Technology,USA; and Joe Marks, Mitsubishi Electric Research Labs, USA

NON RIGID REGISTRATION OF SHAPES VIA DIFFEOMORPHIC POINT MATCHING AND CLUSTERING 3299Laurent Garcin, Institut Geographique National, France; Anand Rangarajan, University of Florida, USA; andLaurent Younes, Johns Hopkins University, USA

ENHANCED MOSAIC BLENDING USING INTRINSIC CAMERA PARAMETERS FROM A ROTATINGAND ZOOMING CAMERA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3303Dae-Woong Kim and Ki-Sang Hong, POSTECH, Korea

FACE ALIGNMENT USING INTRINSIC INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3307Yuchi Huang, National Lab of Pattern Recognition, China; Stephen Lin, Microsoft Research Asia, China; HanqingLu, National Lab of Pattern Recognition, China; and Heung-Yeung Shum, Microsoft Research Asia, China

WAVELET-BASED COLOR FILTER ARRAY DEMOSAICKING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3311Jef Driesen and Paul Scheunders, University of Antwerp, Belgium

SESSION WP-P5: Image Formation II

A 2-LEVEL DOMAIN DECOMPOSITION ALGORITHM FOR INVERSE DIFFUSE OPTICALTOMOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3315Il-Young Son, Murat Guven, Birsen Yazici, Rensselaer Polytechnic Institute, USA; and Xavier Intes, University ofPennsylvania, USA

IMAGE FUSION USING WEIGHTED MULTISCALE FUNDAMENTAL FORM . . . . . . . . . . . . . . . . . . . . . . . . . . . 3319Tao Chen, RuoSan Guo and Silong Peng, Institute of Automation, Chinese Academy of Sciences, China

SPECKLE IMAGE ANALYSIS OF CORTICAL BLOOD FLOW AND PERFUSION USING TEMPORALLYDERIVED CONTRASTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3323Allan Tan, Wanzhen Liu, Yan Seng Elijah Yew, Joseph Suresh Paul and Sim Heng Ong, Department of Electricaland Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore

HYPERSPECTRAL TARGET DETECTION USING KERNEL MATCHED SUBSPACE DETECTOR . . . . . . . . . 3327Heesung Kwon and Nasser M. Nasrabadi, US Army Research Laboratory, USA

HYPERSPECTRAL ANOMALY DETECTION USING KERNEL RX-ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . 3331Heesung Kwon and Nasser M. Nasrabadi, US Army Research Laboratory, USA

A NEW APPLICATION OF TEXTURE UNIT CODING TO MASS CLASSIFICATION FOR MAMMOGRAMS 3335Yuan Chen and Chein-I Chang, UMBC, USA

DISCRIMINATION AND IDENTIFICATION FOR SUBPIXEL TARGETS IN HYPERSPECTRAL IMAGERY 3339Chein-I Chang, Weimin Liu and Chein-Chi Chang, UMBC, USA

A GENERIC METHOD FOR GENERATING MULTISPECTRAL FILTER ARRAYS . . . . . . . . . . . . . . . . . . . . . . . . 3343Lidan Miao, Hairong Qi, University of Tennessee, USA; and Wesley E. Snyder, North Carolina State University,USA

A COMPARATIVE STUDY OF STATISTICAL AND NEURAL METHODS FOR REMOTE-SENSING IMAGECLASSIFICATION AND DECISION FUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3347Safaa Mahmoud, National Authority of Remote Sensing and Space Science, Egypt; Moumen El-Melegy, AssiutUniversity, Egypt; and Aly Farag, University of Louisville, USA

COMPARING COLOR AND TEXTURAL INFORMATION IN VERY HIGH RESOLUTION SATELLITEIMAGE CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3351Ewout Vansteenkiste, Abram Schoutteet, Sidharta Gautama and Wilfried Philips, University of Ghent, Belgium

MULTISENSOR RASTER AND VECTOR DATA FUSION BASED ON UNCERTAINTY MODELING . . . . . . . 3355Sang-Chul Lee and Peter Bajcsy, National Center for Supercomputing Applications, University of Illinois atUrbana-Champaign, USA

SESSION WP-P6: Motion Detection and Estimation: Other Methods

THE EFFECT OF GLOBAL MOTION PARAMETER ACCURACIES ON THE EFFICIENCY OF VIDEOCODING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3359Gokce Dane and Truong Nguyen, University of California, San Diego, USA

EXTENSION OF AAM WITH 3D SHAPE MODEL FOR FACIAL SHAPE TRACKING . . . . . . . . . . . . . . . . . . . . . 3363Jaewon Sung and Daijin Kim, POSTECH, South Korea

A ROBUST AND NON-ITERATIVE ESTIMATION METHOD OF MULTIPLE 2D MOTIONS . . . . . . . . . . . . . . . 3367Eun-Young Kang, California State University, Los Angeles, USA; Isaac Cohen and Gerard Medioni, University ofSouthern California, USA

GRADIENT BASED DOMINANT MOTION ESTIMATION WITH INTEGRAL PROJECTIONS FOR REALTIME VIDEO STABILISATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3371Andrew Crawford, Hugh Denman, Francis Kelly, Francois Pitie and Anil Kokaram, Trinity College, Dublin, Ireland

ROBUST MOTION-BASED IMAGE SEGMENTATION USING FUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3375Michael Farmer, Eaton Corporation, USA; Xiaoguang Lu, Hong Chen and Anil Jain, Michigan State University,USA

ON AUTOMATIC DETERMINATION OF VARYING FOCAL LENGTHS USING SEMIDEFINITEPROGRAMMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3379Motilal Agrawal, SRI International, USA

A SIMPLIFIED METHOD OF ENDOSCOPIC IMAGE DISTORTION CORRECTION BASED ON GREYLEVEL REGISTRATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3383Rosebet Miranda-Luna, Walter Blondel, Christian Daul, Yahir Hernandez, Ruben Posada and Didier Wolf, CRAN-INPL, France

GEOMETRIC CONSTRUCTION OF THE CAUSTIC CURVES FOR CATADIOPTRIC SENSORS . . . . . . . . . . . 3387Siohoi Ieng, Laboratory of Instruments and Systems of Ile de France (LISIF)/ Laboratory of Complex SystemsControl, Analysis and Communication (LACCSC) - ECE, France; and Ryad Benosman, Laboratory of Instrumentsand Systems of Ile de France, France

FOCAL LENGTH SELF-CALIBRATION BASED ON DEGENERATED KRUPPA’S EQUATIONS: METHODAND EVALUATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3391Weilun Lao, Institute for Infocomm Research, Singapore; Zhaolin Cheng, Department of Mechanical Engineer-ing, National University of Singapore, Singapore; Alvin Kam, Institute for Infocomm Research, Singapore; TeleTan, Department of Computing, Curtin University of Technology, Australia; and Ashraf Kassim, Department ofElectrical and Computer Engineering, National University of Singapore, Singapore

LINEAR CAMERA AUTOCALIBRATION WITH VARYING PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3395Antonio Valdes, Departamento de Geometrıa y Topologıa, Universidad Complutense de Madrid, Spain; JoseI. Ronda and Guillermo Gallego, Departamento de Senales, Sistemas y Radiocomunicaciones, UniversidadPolitecnica de Madrid, Spain

MEAN-SHIFT BACKGROUND IMAGE MODELLING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3399Massimo Piccardi and Tony Jan, University of Technology, Sydney, Australia

FUSING VIDEO AND SPARSE DEPTH DATA IN STRUCTURE FROM MOTION. . . . . . . . . . . . . . . . . . . . . . . . . . 3403Qilong Zhang and Robert Pless, Computer Science Dept.,Washington University, USA

MOTION BLUR REMOVAL AND ITS APPLICATION TO VEHICLE SPEED DETECTION. . . . . . . . . . . . . . . . . 3407Huei-Yung Lin and Kun-Jhih Li, National Chung Cheng University, Department of Electrical Engineering, Taiwan

GLOBAL MOTION ESTIMATION FOR MPEG-ENCODED STREAMS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3411Renan Coudray and Bernard Besserer, University La Rochelle, France

SESSION WP-P7: Watermarking and Cryptography

FILTER BANK SELECTION FOR THE OWNERSHIP VERIFICATION OF WAVELET BASED DIGITALIMAGE WATERMARKING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3415Min-Jen Tsai, National Chiao Tung University, Taiwan

REVERSIBLE DATA-EMBEDDING WITH A HIERARCHICAL STRUCTURE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3419Jun Tian and Raymond Wells, International University Bremen, Germany

WATERMARKING ROBUST AGAINST ANALOG VCR RECORDING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3423Koichi Magai, Hiroshi Ito, Mitsuyoshi Suzuki, Kohtaro Asai, Mitsubishi Electric Corporation Information Tech-nology R&D Center, Japan; and Hidetoshi Mishima, Mitsubishi Electric Corporation Advanced Technology R&DCenter, Japan

MULTIRESOLUTION FRAGILE WATERMARKING USING COMPLEX CHIRP SIGNAL FOR CONTENTINTEGRITY VERIFICATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3427Dan Yu, Farook Sattar and Braham Barkat, Nanyang Technological University, Singapore

ENCRYPTION OF WAVELET-CODED IMAGERY USING RANDOM PERMUTATIONS . . . . . . . . . . . . . . . . . . . 3431Roland Norcen and Andreas Uhl, Salzburg University, Austria

A FAST IMAGE-SCRAMBLE METHOD USING PUBLIC-KEY ENCRYPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3435Osamu Watanabe, Akiko Nakazaki and Hitoshi Kiya, Tokyo Metropolitan University, Japan

COMPLIANT ENCRYPTION OF JPEG2000 CODESTREAMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3439Yongdong Wu and Robert H. Deng, Institute for Infocomm Research, Singapore

ROBUST PERCEPTUAL IMAGE HASHING VIA MATRIX INVARIANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3443Suleyman S. Kozat, University of Illinois, Urbana-Champaign, USA; Ramarathnam Venkatesan and M. KivancMihcak, Microsoft Research, USA

PROGRESSIVE PROTECTION OF JPEG2000 CODE-STREAMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3447Yongdong Wu, Di Ma and Robert H. Deng, Institute for Infocomm Research, Singapore

OPTIMAL THRESHOLDING FOR KEY GENERATION BASED ON BIOMETRICS . . . . . . . . . . . . . . . . . . . . . . . 3451Wende Zhang, Carnegie Mellon University, USA; Yao-Jen Chang, Industrial Technology Research Institute, Tai-wan; and Tsuhan Chen, Carnegie Mellon University, USA

SECURITY ANALYSIS FOR KEY GENERATION SYSTEMS USING FACE IMAGES. . . . . . . . . . . . . . . . . . . . . . 3455Wende Zhang, Cha Zhang and Tsuhan Chen, Carnegie Mellon University, USA

A PUBLIC-KEY AUTHENTICATION WATERMARKING FOR BINARY IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . 3459Hae Yong Kim, Universidade de Sao Paulo, Escola Politecnica, Brazil; and Ricardo L. De Queiroz, Universidadede Brasilia, Brazil

HIGH-CAPACITY DATA HIDING IN HALFTONE IMAGES USING MINIMAL ERROR BIT SEARCHING. . 3463Soo-Chang Pei and Jing-Ming Guo, National Taiwan University, Taiwan

SESSION WP-P8: Image Segmentation: Clustering and Statistical Meth-ods

IMAGE SEGMENTATION AS REGULARIZED CLUSTERING: A FULLY GLOBAL CURVE EVOLUTIONMETHOD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3467Carlos Vazquez, Amar Mitiche and Ismail Ben Ayed, INRS-EMT, Canada

AUTOMATIC DETERMINATION OF INTRINSIC CLUSTER NUMBER SEQUENCE IN SPECTRALCLUSTERING USING RANDOM WALK ON GRAPH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3471Xin Zheng and Xueyin Lin, Institute of HCI and Media Integration, Tsinghua University, China

AUTOMATIC CLASSIFICATION OF TEETH IN BITEWING DENTAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . 3475Mohammad Mahoor and Mohamed Abdel-Mottaleb, Department of ECE, University of Miami, USA

EVOLUTIONARY GIBBS SAMPLER FOR IMAGE SEGMENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3479Xiao Wang and Han Wang, Nanyang Technological University, Singapore

SEGMENTATION OF REGIONS IN JPEG COMPRESSED MEDICAL IMAGES . . . . . . . . . . . . . . . . . . . . . . . . . . . 3483Pramod Singh, School of Computer Science and Engineering, University of New South Wales, Australia

BACKGROUND DIFFERENCING TECHNIQUE FOR IMAGE SEGMENTATION BASED ON THE STATUSOF REFERENCE PIXELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3487Toshiyuki Yoshida, Dept. Information Science, Fukui University, Japan

A WAVELET DOMAIN HIERARCHICAL HIDDEN MARKOV MODEL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3491Zhen Ye and Cheng-Chang Lu, Dept. of Computer Science, Kent State University, USA

VISUAL ATTENTION BASED ROI MAPS FROM GAZE TRACKING DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3495Anthony Nguyen, Vinod Chandran and Sridha Sridharan, Queensland University of Technology, Australia

VARIABLE METRIC FOR BINARY VECTOR QUANTIZATION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3499Ismo Karkkainen and Pasi Franti, Department of Computer Science, University of Joensuu, Finland

A HEURISTIC K-MEANS CLUSTERING ALGORITHM BY KERNEL PCA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3503Mantao Xu and Pasi Franti, University of Joensuu, Finland

SESSION WP-P9: Image Scanning, Display, and Printing II

PERCEPTUAL QUALITY METRICS: EVALUATION OF INDIVIDUAL COMPONENTS . . . . . . . . . . . . . . . . . . . 3507Benedicte Fontaine, Hakim Saadane and Adrien Thomas, IRCCyN, France

COLOR VIDEO DEMOSAICKING VIA MOTION ESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3511Xiaolin Wu and Lei Zhang, McMaster University, Canada

LIGHT FIELD COMPRESSION BASED ON PREDICTION PROPAGATING AND WAVELET PACKET . . . . . 3515Xu Dong, Dai Qionghai and Xu Wenli, Department of Automation, Tsinghua University, China

EXPRESSION MORPHING FROM DISTANT VIEWPOINTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3519Tao Fu and Hassan Foroosh, University of Central Florida, USA

MERGING RATIO IMAGES BASED REALISTIC OBJECT CLASS RE-RENDERING . . . . . . . . . . . . . . . . . . . . . . 3523Yun Fu, Institute of Artificial Intelligence and Robotics(AI&R), Xi’an Jiaotong University, China

CAMERA BASED EVALUATION OF PHOTOMETRIC COMPENSATION METHODS ON MULTI-PROJECTOR DISPLAYS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3527Aditi Majumder, University of California, Irvine, USA

VIDEO QUALITY METRIC FOR LOW BITRATE COMPRESSED VIDEOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3531Ee Ping Ong, Xiaokang Yang, Weisi Lin, Zhongkang Lu and Susu Yao, Institute for Infocomm Research, Singapore

A FINE-STRUCTURE IMAGE/VIDEO QUALITY MEASURE USING LOCAL STATISTICS . . . . . . . . . . . . . . . . 3535Kyungnam Kim and Larry Davis, Dept. of Computer Science, Univ. of Maryland, College Park, USA

NO REFERENCE QUALITY ASSESSMENT FOR JPEG2000 COMPRESSED IMAGES. . . . . . . . . . . . . . . . . . . . . 3539Hanghang Tong, Tsinghua University, China; Mingjing Li, Hongjiang Zhang, Microsoft Research Asia, China;and Changshui Zhang, Tsinghua University, China

SEGMENTATION-DRIVEN PERCEPTUAL QUALITY METRICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3543Andrea Cavallaro, Queen Mary University of London, UK; and Stefan Winkler, Genista Corporation, Switzerland

HALFTONE/CONTONE CONVERSION USING NEURAL NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3547Win-Bin Huang, Yen-Wei Lu, Yau-Hwang Kuo, Alvin W.Y. Su and Wei-Chen Chang, Dept. of Computer Scienceand Information Engineering, National Cheng Kung University, Taiwan