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Surface Light Fields for 3D Photography

Surface Light Fields for 3D Photography. Daniel N. Wood University of Washington SIGGRAPH 2001 Course. Collaborators ( and co-authors on SIGGRAPH 2000 paper ). Daniel Azuma Wyvern Aldinger Brian Curless Tom Duchamp David Salesin Werner Stuetzle University of Washington. Outline.

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Surface Light Fields for 3D Photography

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  1. Surface Light Fieldsfor 3D Photography Daniel N. Wood University of Washington SIGGRAPH 2001 Course

  2. Collaborators(and co-authors on SIGGRAPH 2000 paper) Daniel Azuma Wyvern Aldinger Brian Curless Tom Duchamp David Salesin Werner Stuetzle University of Washington

  3. Outline • Surface light field representation • Compression primer • Surface light fields for 3D photography • With details of compression • And a preliminary look at a new compression algorithm

  4. Surface light fields

  5. Lumisphere-valued “texture” maps Lumisphere

  6. q s Surface light fields in flatland

  7. q s Surface light fields in flatland

  8. q s Surface light fields in flatland

  9. Compression primer • Singular value decomposition(or principal components analysis) • Handling color • Using regions • Reflection parameterization • Vector quantization • Others… (Wavelets, DCT)

  10. Singular value decomposition U VT  SLF

  11. SVD in two matrices Eigen Lumispheres Eigen Textures SLF

  12. First eigenvectors Eigen Lumispheres Eigen Textures SLF First eigentexture and corresponding first eigenlumisphere

  13. ~ ~ Truncated SVD Eigen-lumisphere = Eigen-texture Outer product of first eigen-texture and first eigen-lumisphere is closest rank 1 (separable) matrix.

  14. Handling color Separate matrices Colors in directions (rows) Colors in surface texture (columns)

  15. Handling color Separate matrices Colors in directions (rows) Colors in surface texture (columns) Chen et al. Wood et al. Nishino et al.

  16. SVD in color Eigen Lumispheres Eigen Textures SLF

  17. Zooming in… Eigen Lumispheres Eigen Textures SLF

  18. Zoom into important vectors ... . . . SLF

  19. Reconstruction using SVD Original Rank 1 Rank 7 (1:20)

  20. Surface light field structure Rows are points on surface What are the columns? And, can they be made more coherent?

  21. Surface light field structure • Rows are points on surface • Increasing column coherence: • Break into regions, and / or • Use reflection parameterization

  22. Separate SVD for regions Eigen Lumispheres Eigen Textures Eigen Lumispheres Eigen Textures

  23. Reconstruction using regions Original One region (Rank 5) Two regions (Rank 5)

  24. Reflection reparameterization

  25. Reflection reparameterization

  26. Reflection reparameterization

  27. Un-reflected Reflected Reflection in flatland* *sort of

  28. q q Reflection doesn’t happenin the plane Un-reflected Reflected

  29. Reflection in 3 space Un-reflected Reflected

  30. Reflection in “flatland” Un-reflected Reflected Original Rank 5 Original Rank 5

  31. Other compression strategies • Discrete cosine transform [ Miller et al. 1999– Eurographics Workshop on Rendering] • Vector quantization [ Wood et al. 2000 - SIGGRAPH ] • Wavelet decomposition [ Magnor and Girod 2000 - SPIE VCIP]

  32. Vector quantization (unreflected) Uncompressed Codebook Vector- quantized

  33. Vector quantization (reflected) Uncompressed Codebook Vector- quantized

  34. Surface light fields for 3D photography(SIGGRAPH 2000) • Goals • Rendering and editing • Inputs • Photographs and geometry • Requirements • Estimation and compression

  35. Overview Data acquisition Estimation and compression Rendering Editing

  36. Overview Data acquisition Estimation and compression Rendering Editing

  37. Scan and reconstruct geometry Range scans (only a few shown . . .) Reconstructed geometry

  38. Take photographs Camera positions Photographs

  39. Register photographs to geometry Photographs Geometry

  40. Register photographs to geometry User selected correspondences (rays)

  41. Parameterizing the geometry Map Scanned geometry Base mesh

  42. Sample base mesh faces Base mesh Detailed geometry

  43. Assembling data lumispheres Data lumisphere

  44. Overview Data acquisition Estimation and compression Rendering Editing

  45. Pointwise fairing Faired lumisphere Data lumisphere

  46. Pointwise fairing results Pointwise faired (177 MB) Input photograph

  47. Pointwise fairing Many faired lumispheres Many input data lumispheres

  48. Compression Small set of prototypes

  49. Compression / Estimation Many input data lumispheres Small set of prototypes

  50. Median removal Reflected Median (“diffuse”) + + Median-removed (“specular”)

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