1. . Wild Dreams for Cameras Jack Tumblin Northwestern University jet@cs.northwestern.edu jet@cs.northwestern.edu From May 24 Panel Discussion on cameras at Symposium on Computational Photography & Video May 23-25, 2005

2. Definitions Visual Appearance: What we think we see. (Consciously-available estimates of our surroundings, made from the light reaching our eyes) Picture: A ‘container’ for visual appearance. (something we make to hold what we see, or what would like to see) Image: A copy of light intensities. (Just one kind of picture, made by copying a scaled map of scene light intensities as a lens might)

3.  “Machine-Readable” Images? scene scene display SceneLightIntensities DisplayLightIntensities ‘Pixel values’ (scene intensity? display intensity? (scene intensity? display intensity? perceived intensity? ‘blackness/whiteness’ ?) perceived intensity? ‘blackness/whiteness’ ?) display

4. Display RGB(x,y,t n ) Image I(x,y,λ,t) Rendering 3D Scene light sources, BRDFs, shapes, positions, movements, …Eyepoint position, movement, projection, … PHYSICAL Scene light sources, BRDFs, shapes, positions, movements, …Eyepoint position, movement, projection, … PERCEIVED Vision Digital Images Exposure’ or Tone Mapping

5. Something Else? Display RGB(x,y,t n ) Image I(x,y,λ,t) Rendering 3D Scene light sources, BRDFs, shapes, positions, movements, …Eyepoint position, movement, projection, … PHYSICAL Scene light sources, BRDFs, shapes, positions, movements, …Eyepoint position, movement, projection, … PERCEIVED Vision ‘Digital Pictures?’

6. Williams 1998: ‘Inflated Silhouettes’ http://graphics.stanford.edu/workshops/ibr98/#Schedule%20of%20sessions 2D Photo Silhouette  ‘Inflate’ Depth  Symmetry

7. Williams`98: ‘Inflated Silhouettes’ Not bad! How can we do better? http://graphics.stanford.edu/workshops/ibr98/#Schedule%20of%20sessionshttp://graphics.stanford.edu/workshops/ibr98/#Schedule%20of%20sessionshttp://graphics.stanford.edu/workshops/ibr98/#Schedule%20of%20sessions

8. Malzbender, HPlabs 2001 A Mostly 2-D Method Polynomial Texture Maps Store just 6 coefficients at each pixel, get Interactive re-lighting...

9. 3D: Try image + other dimensions Halle: Multiple Viewpoint Rendering (SIGG98) http://web.media.mit.edu/~halazar/sig98/halle98.pdfHalle: Multiple Viewpoint Rendering (SIGG98) http://web.media.mit.edu/~halazar/sig98/halle98.pdf http://web.media.mit.edu/~halazar/sig98/halle98.pdf

10. Oh et. al, 2001: 2D  3D Manually Guided—7 Hours!Manually Guided—7 Hours! ? Would a more varied for camera pose help? http://graphics.lcs.mit.edu/ibedit/ibedit_s2001_cameraReady.pdf? Would a more varied for camera pose help? http://graphics.lcs.mit.edu/ibedit/ibedit_s2001_cameraReady.pdf http://graphics.lcs.mit.edu/ibedit/ibedit_s2001_cameraReady.pdf

11. Bixels (bilinear) Bixels: Picture Samples With Embedded Sharp Boundaries Jack Tumblin and Prasun Choudhury Northwestern University, Evanston IL, USA Pixels (bilinear)

12. Results: boundary=depth discontinuity (Source data courtesy Ramesh Raskar, MERL) Source (1100x800) Boundaries (50x65)

13. Results: boundary=depth discontinuity (Source data courtesy Ramesh Raskar, MERL) Bixels (bilinear) 50x65 Pixels (bilinear) 50x65