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Keywords: Signal processing, Applied optics, Computer graphics and vision, Electronics, Art, and Online photo collectionsA computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes.We will learn about the complete camera pipeline. In several hands-on projects we will build several physical imaging prototypes and understand how each stage of the imaging process can be manipulated.We will learn about modern methods for capturing and sharing visual information. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded -- beyond those present in traditional protographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.In this couse we will study this emerging multi-disciplinary field -- one which is at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. We will examine whether such innovative camera-like sensors can overcome the tough problems in scene understanding and generate insightful awareness. In addition, we will develop new algorithms to exploit unusual optics, programmable wavelength control, and femto-second accurate photon counting to decompose the sensed values into perceptually critical elements.
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2. http://scalarmotion.wordpress.com/2009/03/15/propeller-image-aliasing/ 3. Shower Curtain: Diffuser Direct Global 4. Shower Curtain: Diffuser Direct Global 5. A Teaser: Dual Photography Scene Photocell Projector 6. A Teaser: Dual Photography Scene Photocell Projector 7. A Teaser: Dual Photography Scene Photocell Projector 8. A Teaser: Dual Photography Scene Photocell Projector Camera 9. camera The 4D transport matrix: Contribution of each projector pixel to each camera pixel scene projector 10. camera The 4D transport matrix: Contribution of each projector pixel to each camera pixel scene projector Sen et al, Siggraph 2005 11. camera The 4D transport matrix: Which projector pixel contribute to each camera pixel scene projector Sen et al, Siggraph 2005 ? 12. Dual photography from diffuse reflections:Homework Assignment 2 the cameras view Sen et al, Siggraph 2005 13. Digital cameras are boring:Film-like Photography
14. Improving FILM-LIKECamera Performance
15.
16. Can you look around a corner ? 17. Convert LCD into a big flat camera? Beyond Multi-touch 18. Medical Applications of Tomography bone reconstruction segmented vessels Slides by Doug Lanman 19. Camera Culture RameshRaskar Camera Culture 20. Computational Illumination Curved Planar Non-planar Single Projector Multiple Projectors Pocket-Proj Objects 1998 1998 2002 2002 1999 2002 2003 1998 1997 Computational Photography My Background Projector j User : T ? 21. Questions
22. Approach
23. Plan
24. What is Computational Camera ? -Generate photos that cannot be creates by a singlecamera at a single instant -Create theultimate camerathat mimics the eye -Createimpossible photosthat dont mimic the eye -Learn from scientific imaging (tomography, coded aperture, coherence, phase-contrast) 25. Fernald,Science [Sept 2006] Shadow Refractive Reflective Toolsfor Visual Computing 26. Traditionalfilm-like Photography Lens Detector Pixels Image Slide by Shree Nayar 27. ComputationalCamera :Optics, Sensors and Computations Generalized Sensor Generalized Optics Computations 4D Ray Bender Upto 4DRay Sampler Ray Reconstruction Raskar and Tumblin Picture 28. Novel Cameras Generalized Sensor Generalized Optics Processing 29. Programmable Lighting Novel Cameras Scene Generalized Sensor Generalized Optics Processing Generalized Optics Light Sources Modulators 30. Motivation
31. Motivation
32. Cameras Everywhere
33. Cameras Everywhere 34. Where are the cameras? 35. Where are the cameras? 36. Inflection Point in Camera Usage 37. 38. DIY Green Screen Effects $160 Panasonic Beauty Appliance Minoru Webcam 39. Fujifilm FinePix 3D (stereo) GigaPan Epic 100 40. Simply getting depth is challenging ! Godin et al.An Assessment of Laser Range Measurement on Marble Surfaces . Intl. Conf. Optical 3D Measurement Techniques, 2001M. Levoy.Why is 3D scanning hard? 3DPVT, 2002
Lanman and Taubin09 41. Contact Non-Contact Active Passive Transmissive Reflective Shape-from-X (stereo/multi-view, silhouettes, focus/defocus, motion, texture, etc.) Active Variants of Passive Methods (stereo/focus/defocus using projected patterns)Time-of-Flight Triangulation (laser striping and structured lighting) Computed Tomography (CT) Transmissive Ultrasound Direct Measurements (rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM) Non-optical Methods (reflective ultrasound, radar, sonar, MRI) Taxonomy of 3D Scanning: Lanman and Taubin09 42. DARPA Grand Challenge 43. Do-It-Yourself (DIY) 3D Scanners Lanman and Taubin09 44. What is interesting here?Social voting in the real world = popular 45. Pantheon 46. How do we move through a space? 47. Computational Photography[Raskar and Tumblin]
capturesa machine-readable representation of our world to hyper-realisticallysynthesizethe essence of our visual experience. 48. Goal and Experience Low Level Mid Level High Level Hyper realism Raw Angle, spectrum aware Non-visual Data, GPS Metadata Priors Comprehensive 8D reflectance field Digital Epsilon Coded Essence CP aims to make progress on both axis Camera Array HDR,FoV Focal stack Decomposition problems Depth Spectrum LightFields Human Stereo Vision Transient Imaging Virtual Object Insertion Relighting Augmented Human Experience Material editing from single photo Scene completion from photos Motion Magnification Phototourism 49. 50.
51. Visual Social Computing
? Raskar 2008 52. Goals
53. Vein Viewer(Luminetx)
54. Vein Viewer(Luminetx)
Coaxial IR camera + Projector 55. 56. Beyond Visible Spectrum Cedip RedShift 57.
58. What is the emphasis?
59. Pre-reqs
60.
61. 2 Sept 18th Modern Optics and Lenses, Ray-matrix operations3 Sept 25th Virtual Optical Bench, Lightfield Photography, Fourier Optics, Wavefront Coding 4 Oct 2nd Digital Illumination , Hadamard Coded and Multispectral Illumination5 Oct 9th Emerging Sensors : High speed imaging, 3D range sensors, Femto-second concepts, Front/back illumination, Diffraction issues6 Oct 16th Beyond Visible Spectrum:Multispectral imaging and Thermal sensors, Fluorescent imaging, 'Audio camera' 7 Oct 23rd Image Reconstruction Techniques, Deconvolution, Motion and Defocus Deblurring, Tomography, Heterodyned Photography, Compressive Sensing 8 Oct 30th Cameras for Human Computer Interaction (HCI): 0-D and 1-D sensors, Spatio-temporal coding, Frustrated TIR, Camera-display fusion9 Nov 6th Useful techniques in Scientific and Medical Imaging: CT-scans, Strobing, Endoscopes, Astronomy and Long range imaging 10 Nov 13th Mid-term Exam,Mobile Photography, Video Blogging, Life logs and Online Photo collections11 Nov 20th Optics and Sensing in Animal Eyes. What can we learn from successful biological vision systems? 12 Nov 27th Thanksgiving Holiday (No Class) 13 Dec 4th Final Projects 62. Topics not covered
63. Courses related to CompCamera
64. Questions .. 65.
66. Goals
67. 2 ndInternational Conference onComputational Photography Papers dueNovember 2, 2009 http://cameraculture.media.mit.edu/iccp10 68. Writing a Conference Quality Paper
69. How to quickly get started writing a paper
70. Casio EX F1
71. 72. Cameras and Photography Art,Magic,Miracle 73. Topics
74. Debevec et al. 2002: Light Stage 3 75. Image-Based Actual Re-lighting Film the background in Milan, Measure incoming light, Light the actress in Los Angeles Matte the background Matched LA and Milan lighting. Debevec et al., SIGG2001 76. Can you look around a corner ? 77. Can you look around a corner ? Kirmani, Hutchinson, Davis, Raskar 2009 Accepted for ICCV2009,Oct 2009 in Kyoto Impulse Response of a Scene cameraculture.media.mit.edu/femtotransientimaging 78. Femtosecond Laser as Light Source Pico-second detector array as Camera 79. AreBOTHa photograph? Rollout Photographs Justin Kerr:Slide idea: Steve Seitz http://research.famsi.org/kerrmaya.html 80. Part 2:Fast Forward Preview 81. Synthetic Lighting Paul Haeberli, Jan 1992 82. Homework
83. Debevec et al. 2002: Light Stage 3 84. Image-Based Actual Re-lighting Film the background in Milan, Measure incoming light, Light the actress in Los Angeles Matte the background Matched LA and Milan lighting. Debevec et al., SIGG2001 85. Depth Edge Camera 86. Ramesh Raskar, Karhan Tan, Rogerio Feris,Jingyi Yu, Matthew Turk Mitsubishi Electric Research Labs (MERL), Cambridge, MA U of California at Santa Barbara U of North Carolina at Chapel Hill Non-photorealistic Camera:Depth Edge DetectionandStylized Renderingusing Multi-Flash Imaging 87. 88. 89. 90. 91. Depth Discontinuities Internal and external Shape boundaries, Occluding contour, Silhouettes 92. DepthEdges 93. Our Method Canny 94. A Night Time Scene:Objects are Difficult to Understand due to Lack of ContextDark Bldgs Reflections on bldgs Unknown shapes 95. Enhanced Context : All features from night scene are preserved, but background in clear Well-lit Bldgs Reflections in bldgs windows Tree, Street shapes 96. Background is captured from day-time scene using the same fixed cameraNight ImageDay Image Result: Enhanced Image 97. Participatory Urban Sensing
http://research.cens.ucla.edu/areas/2007/Urban_Sensing/ (Erin Brockovich) n 98. Crowdsourcing http://www.wired.com/wired/archive/14.06/crowds.html Object Recognition Fakes Template matching Amazon Mechanical Turk:Steve Fossett search ReCAPTCHA=OCR 99. 100. Community Photo Collections U of Washington/Microsoft: Photosynth 101. GigaPixel Images Microsoft HDView http://www.xrez.com/owens_giga.html http://www.gigapxl.org/ 102. Optics
103. Assignment 2
104. Light Field Inside a Camera 105. Lenslet-based Light Field camera [Adelson and Wang, 1992, Ng et al. 2005 ] Light Field Inside a Camera 106. Stanford Plenoptic Camera[Ng et al 2005]
Contax medium format camera Kodak 16-megapixel sensor Adaptive Optics microlens array 125 square-sided microlenses 107. DigitalRefocusing [Ng et al 2005] Can we achieve this with aMaskalone? 108. Mask based Light Field Camera [Veeraraghavan, Raskar, Agrawal, Tumblin, Mohan, Siggraph 2007 ] Mask Sensor 109. How to Capture4DLight Field with2DSensor ? What should be thepatternof the mask ? 110. Radio Frequency Heterodyning Receiver: Demodulation High Freq Carrier 100 MHz Reference Carrier Incoming Signal 99 MHz Baseband Audio Signal 111. Optical Heterodyning Photographic Signal (Light Field) CarrierIncident Modulated Signal Reference Carrier Main Lens Object Mask Sensor Recovered LightField Software Demodulation Baseband Audio Signal Receiver: Demodulation High Freq Carrier 100 MHz Reference Carrier Incoming Signal 99 MHz 112. Captured 2D Photo Encoding due to Mask 113. 1/f 0 Mask Tile Cosine Mask Used 114. f Modulated Light Field f x f 0 f x0 Modulation Function Sensor Slice captures entire Light Field 115. 2D FFT Traditional Camera Photo Heterodyne Camera Photo Magnitude of 2D FFT 2D FFT Magnitude of 2D FFT 116. Computing 4D Light Field 2D Sensor Photo, 1800*1800 2D Fourier Transform, 1800*1800 2D FFT Rearrange 2D tiles into 4D planes 200*200*9*9 4D IFFT 4D Light Field 9*9=81 spectral copies 200*200*9*9 117. Agile Spectrum Imaging With Ankit Mohan, Jack Tumblin [Eurographics 2008] 118. Lens Glare Reduction[Raskar, Agrawal, Wilson, Veeraraghavan SIGGRAPH 2008]
119. Glare Reduction/Enhancement using4D Ray Sampling Captured Glare Reduced Glare Enhanced 120.
i j x Sensor u 121. Long-range synthetic aperture photography Levoy et al., SIGG2005 122. Synthetic aperture videography 123. Focus Adjustment: Sum of Bundles 124. Synthetic aperture photography Smaller aperture less blur, smaller circle of confusion 125. Synthetic aperture photography Merge MANY cameras to act as ONE BIG LENS Small items are so blurrythey seem to disappear.. 126. Coded Aperture http://users.ameritech.net/paulcarlisle/codedaperture.html EncodingMURA pattern Decoding pattern MultiplePinholes 127. Light field photography using a handheld plenoptic camera Ren Ng, Marc Levoy, Mathieu Brdif, Gene Duval, Mark Horowitz and Pat Hanrahan 128. Prototype camera
Contax medium format camera Kodak 16-megapixel sensor Adaptive Optics microlens array 125 square-sided microlenses 129. 130. Example of digital refocusing 131. Extending the depth of fieldconventional photograph, main lens atf/ 22 conventional photograph, main lens atf/ 4 light field, main lens atf/ 4, after all-focus algorithm [Agarwala 2004] 132. Imaging in Sciences:Computer Tomography
133. Borehole tomography
(from Reynolds) 134. Deconvolution microscopy
ordinary microscope image deconvolved from focus stack 135. Coded-Aperture Imaging
136. Mask in a Camera Mask Aperture Canon EF 100 mm 1:1.28 Lens, Canon SLR Rebel XT camera 137. Digital Refocusing Captured Blurred Image 138. Digital Refocusing Refocused Image on Person 139. Digital Refocusing 140. Larval Trematode Worm 141. Mask? Sensor 4D Light Field from 2D Photo:Heterodyne Light Field Camera Full Resolution Digital Refocusing: Coded Aperture Camera Mask? Sensor Mask Sensor Mask? Sensor Mask Sensor 142. Coding and Modulation in Camera Using Masks Coded Aperture for Full Resolution Digital Refocusing Heterodyne Light Field Camera Mask? Sensor Mask Sensor Mask Sensor 143. Digital Refocusing Only cone in focus Captured Photo 144. Slides by Todor Georgiev 145. Slides by Todor Georgiev 146. Slides by Todor Georgiev 147. Conventional Lens: Limited Depth of Field OpenAperture Slides by Shree Nayar SmallerAperture 148. Wavefront Coding using Cubic Phase Plate " Wavefront Coding: jointly optimized optical and digital imaging systems ,E. Dowski, R. H. Cormack and S. D. Sarama ,Aerosense Conference, April 25, 2000 Slides by Shree Nayar 149. Depth Invariant Blur Conventional SystemWavefront Coded SystemSlides by Shree Nayar 150. Typical PSF changes slowly Designed PSF changes fast Decoding depth via defocus blur Design PSF that changes quickly through focus so that defocus can be easily estimated Implementation using phase diffractive mask (Sig 2008, Levin et al used amplitude mask) Phase mask R. Piestun, Y. Schechner, J. Shamir, Propagation-Invariant Wave Fields with Finite Energy, JOSA A17, 294-303 (2000) R. Piestun, J. Shamir, Generalized propagation invariant wave-fields, JOSA A 15, 3039 (1998) 151. Rotational PSF R. Piestun, Y. Schechner, J. Shamir, Propagation-Invariant Wave Fields with Finite Energy, JOSA A17, 294-303 (2000) R. Piestun, J. Shamir, Generalized propagation invariant wave-fields, JOSA A 15, 3039 (1998) 152. Can we deal with particle-wave duality of light with modern Lightfield theory ? Youngs Double Slit Expt first null(OPD = /2) Diffraction and Interferences modeled using Ray representation 153. Light Fields
Goal: Representing propagation, interaction and image formation of light usingpurely position and angle parameters Reference plane position direction 154. Light Fields for Wave Optics Effects Wigner Distribution Function Light Field LF < WDF Lacks phase properties Ignores diffraction, phase masks Radiance = Positive ALF ~ WDF Supports coherent/incoherent Radiance = Positive/Negative Virtual light sources Light Field Augmented Light Field WDF 155. Limitations of Traditional Lightfields Wigner Distribution Function Traditional Light Field ray optics based simple and powerful rigorous but cumbersome wave optics based limited in diffraction & interference holograms beam shaping rotational PSF 156. Example: New Representations Augmented Lightfields Wigner Distribution Function Traditional Light Field WDF Traditional Light Field Augmented LF Interference & Diffraction Interaction w/ optical elements ray optics based simple and powerful limited in diffraction & interference rigorous but cumbersome wave optics based Non-paraxial propagation http://raskar.scripts.mit.edu/~raskar/lightfields/ 157. (ii) Augmented Light Field with LF Transformer WDF Light Field Augmented LF Interaction at the optical elements Augmenting Light Field to Model Wave Optics Effects, [Oh, Barbastathis, Raskar] LF propagation (diffractive) optical element LF LF LF LF LF propagation light field transformer negative radiance 158. Virtual light projector with real valued (possiblynegativeradiance) along a ray real projector real projector first null(OPD = /2) virtual light projector Augmenting Light Field to Model Wave Optics Effects, [Oh, Barbastathis, Raskar] 159. (ii) ALF with LF Transformer 160. Origami Lens: Thin Folded Optics (2007) Ultrathin Cameras Using Annular Folded Optics, E. J.Tremblay , R. A. Stack, R. L. Morrison, J. E.Ford Applied Optics , 2007 - OSASlides by Shree Nayar 161. Gradient Index (GRIN) Optics Conventional Convex Lens Gradient Index Lens Continuous change of the refractive index within the optical material Constant refractive index but carefully designed geometric shape Refractive Indexalong width n x Change in RI is very small, 0.1 or 0.2 162. Photonic Crystals
163. Schlieren Photography
Knife edge blocks half the lightunlessdistorted beam focuses imperfectly CollimatedLightCamera 164. http://www.mne.psu.edu/psgdl/FSSPhotoalbum/index1.htm 165. Varying Polarization Yoav Y. Schechner, Nir Karpel 2005 Best polarization state Worst polarization state Best polarizationstate Recoveredimage [Left] The raw images taken through a polarizer. [Right] White-balanced results:The recovered image is much clearer, especially at distant objects, than the raw image 166. Varying Polarization
167. Photon-x:Polarization Bayer Mosaic forSurface normals 168. Foveon: Thick Sensor 169. Novel Sensors
170.
171. Single Pixel Camera 172. Compressed Imaging Scene X AggregateBrightness Y A New Compressive Imaging Camera Architecture D. Takhar et al. ,Proc. SPIE Symp. on Electronic Imaging, Vol. 6065, 2006. Sparsity of Image:sparse basis coefficients measurementbasis Measurements: 173. Single Pixel Camera Image on the DMD 174. Example 4096 Pixels 1600 Measurements (40%)65536 Pixels 6600 Measurements (10%)Original Compressed Imaging 175. Example 4096 Pixels 800 Measurements (20%)4096 Pixels 1600 Measurements (40%)Original Compressed Imaging 176. Line Scan Camera: PhotoFinish 2000 Hz 177. 178. The CityBlock Project Precursor to Google Streetview Maps 179. Figure 2 results Input Image Problem: Motion Deblurring 180. Image Deblurred by solving a linear system. No post-processing Blurred Taxi 181. Application: Aerial Imaging Long Exposure :The moving camera creates smear Time Shutter Open Shutter Closed Short Explosure : Avoids blur. But the image is dark Time Time Shutter Open Shutter Closed Goal: Capturesharp imagewith sufficientbrightnessusing a camera on a fast moving aircraft Sharpness versus Image Pixel Brightness Time Shutter Open Shutter Closed Solution:Flutter Shutter Time = 0 Time = T 182. Application: Electronic Toll Booths Time Goal: Automatic number plate recognition from sharp imageMonitoring Camera for detecting license plates Time Shutter Open Shutter Closed Solution:Sufficiently long exposure duration with fluttered shutter Ideal exposure duration depends on car speed which is difficult to determine a-priory. Longer exposure duration blurs the license plate image making character recognition difficult 183. Fluttered Shutter Camera Raskar, Agrawal, Tumblin Siggraph2006 Ferroelectric shutter in front of the lens is turned opaque or transparent in a rapid binary sequence 184. Short Exposure Traditional MURA Coded Coded Exposure Photography:Assisting Motion Deblurring using Fluttered Shutter Raskar, Agrawal, Tumblin (Siggraph2006) DeblurredResults CapturedPhotos Shutter Result has Banding Artifacts and some spatial frequencies are lost Decoded image is as good as image of a static scene Image is darkand noisy 185. 186. Compound Lens of Dragonfly 187. TOMBO:Thin Camera (2001) Thin observation module by bound optics (TOMBO), J. Tanida, T. Kumagai, K. Yamada, S. Miyatake Applied Optics, 2001 188. TOMBO:Thin Camera 189. ZCam (3Dvsystems),Shuttered Light Pulse Resolution :1cm for 2-7 meters 190. Graphics can inserted behind and between characters 191. Cameras for HCI
192. Boring Camera HCI Projects
193. Cameras for HCI
Han, J. Y. 2005. Low-Cost Multi-Touch Sensing through Frustrated Total Internal Reflection. InProceedings of the 18th Annual ACM Symposium on User Interface Software and Technology 194. Converting LCD Screen = large Camera for 3D Interactive HCI and Video Conferencing Matthew Hirsch, Henry Holtzman Doug Lanman, Ramesh Raskar Siggraph Asia 2009 Class Project in CompCam 2008 SRC Winner BiDi Screen * 195. Beyond Multi-touch: Mobile Laptops Mobile 196. Light Sensing Pixels in LCD Display with embedded optical sensors Sharp Microelectronics Optical Multi-touch Prototype 197. Design Overview Display with embedded optical sensors LCD ,displaying mask Optical sensor array ~2.5 cm ~50 cm 198. Beyond Multi-touch: Hover Interaction
199. Design Vision Object Collocated Capture and Display Bare Sensor Spatial Light Modulator 200. Touch + Hover using Depth Sensing LCD Sensor 201. Overview: Sensing Depth fromArray of Virtual Cameras in LCD 202.
http://www.acreo.se/upload/Publications/Proceedings/OE00/00-KAURANEN.pdf 203.
Computational Probes:Long Distance Bar-codes Mohan, Woo,Smithwick, Hiura, Raskar Accepted as Siggraph 2009 paper 204. Bokode 205. Barcodes markersthat assist machines in understanding the real world 206. Bokode: ankit mohan, grace woo, shinsaku hiura, quinn smithwick, ramesh raskar camera culture group, MIT media lab imperceptible visual tags for camera based interaction from a distance 207. Defocus blur of Bokode 208. Image greatly magnified. Simplified Ray Diagram 209. Our Prototypes 210. street-view tagging 211. Vicon Motion Capture High-speedIR Camera Medical Rehabilitation Athlete Analysis Performance Capture Biomechanical Analysis 212. R Raskar, H Nii, B de Decker, Y Hashimoto, J Summet, D Moore, Y Zhao, J Westhues, P Dietz, M Inami, S Nayar, J Barnwell, M Noland, P Bekaert, V Branzoi, E Bruns Siggraph 2007 Prakash: Lighting-Aware Motion Capture Using Photosensing Markers and Multiplexed Illuminators 213. Imperceptible Tags under clothing, tracked under ambient light HiddenMarker Tags Outdoors Unique Id http://raskar.info/prakash 214. Camera-based HCI
215. Computational Imaging in the Sciences
Slides by Doug Lanman 216. Computational Imaging in the Sciences
Slides by Doug Lanman 217. What is Tomography?
Parallel-beam Tomography Fan-beam Tomography Slides by Doug Lanman 218. Reconstruction: Filtered Backprojection
x y f y f x P (t) P (t,s) G ( ) g(x,y) Slides by Doug Lanman 219. Medical Applications of Tomography bone reconstruction segmented vessels Slides by Doug Lanman 220. Biology: Confocal Microscopy pinhole light source photocell pinhole Slides by Doug Lanman 221. Confocal Microscopy Examples Slides by Doug Lanman 222. Forerunners .. Mask Sensor Mask Sensor 223. Fernald,Science [Sept 2006] Shadow Refractive Reflective Toolsfor Visual Computing 224. Project Assignments
225. Synthetic Lighting Paul Haeberli, Jan 1992 226. Image-Based Actual Re-lighting Film the background in Milan, Measure incoming light, Light the actress in Los Angeles Matte the background Matched LA and Milan lighting. Debevec et al., SIGG2001 227. Dual photography from diffuse reflections:Homework Assignment 2 the cameras view Sen et al, Siggraph 2005 228. Shower Curtain: Diffuser Direct Global 229.
230. Beyond Visible Spectrum Cedip RedShift 231. Goals
232. First Assignment: Synthetic Lighting Paul Haeberli, Jan 1992 233.
234.
235. 2 Sept 18th Modern Optics and Lenses, Ray-matrix operations3 Sept 25th Virtual Optical Bench, Lightfield Photography, Fourier Optics, Wavefront Coding 4 Oct 2nd Digital Illumination , Hadamard Coded and Multispectral Illumination5 Oct 9th Emerging Sensors : High speed imaging, 3D range sensors, Femto-second concepts, Front/back illumination, Diffraction issues6 Oct 16th Beyond Visible Spectrum:Multispectral imaging and Thermal sensors, Fluorescent imaging, 'Audio camera' 7 Oct 23rd Image Reconstruction Techniques, Deconvolution, Motion and Defocus Deblurring, Tomography, Heterodyned Photography, Compressive Sensing 8 Oct 30th Cameras for Human Computer Interaction (HCI): 0-D and 1-D sensors, Spatio-temporal coding, Frustrated TIR, Camera-display fusion9 Nov 6th Useful techniques in Scientific and Medical Imaging: CT-scans, Strobing, Endoscopes, Astronomy and Long range imaging 10 Nov 13th Mid-term Exam,Mobile Photography, Video Blogging, Life logs and Online Photo collections11 Nov 20th Optics and Sensing in Animal Eyes. What can we learn from successful biological vision systems? 12 Nov 27th Thanksgiving Holiday (No Class) 13 Dec 4th Final Projects 236. What is the emphasis?
237. First Homework Assignment
238. Goal and Experience Low Level Mid Level High Level Hyper realism Raw Angle, spectrum aware Non-visual Data, GPS Metadata Priors Comprehensive 8D reflectance field Digital Epsilon Coded Essence CP aims to make progress on both axis Camera Array HDR,FoV Focal stack Decomposition problems Depth Spectrum LightFields Human Stereo Vision Transient Imaging Virtual Object Insertion Relighting Augmented Human Experience Material editing from single photo Scene completion from photos Motion Magnification Phototourism 239.
Computational Photography http://raskar.info/photo/ 240. 241. Blind Camera Sascha Pohflepp,U of the Art, Berlin, 2006 242. END