Institute of Computer Science II
Computer Graphics
Realistic Object Appearance using
Bidirectional Texture Functions
Chris...
INTRODUCTION
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz2 20/10/2011
Object Appearance
• Common presentation: Geometry (+ Texture)
• … but is this sufficient?
3D COFORM STAR – VAST 2011 Prato...
Importance of Surface Appearance
• Same shape, different materials
• Different „look-and-feel“
• Important hints about the...
Object Appearance
• Impression of reflection of
incident light
• Influenced by features on
different scales
• Macroscopic
...
Form of Representation
Macroscopic scale
•3D shape
•Explicit representation
(e.g. polygon mesh)
Mesoscopic scale
•Individu...
Bidirectional Reflectance Distribution Function
• Opaque, uniform
Materials
• No texture!
• Ratio of incident
irradiance t...
Bidirectional Reflectance Distribution Function
• Example BRDF
• sampled at discrete angles
3D COFORM STAR – VAST 2011 Pra...
Model-driven vs. Data-driven
• Matusik et al. 2003 [1]:
Measured BRDF ground-truth data
• 100 real world materials
• 1° re...
Model-driven vs. Data-driven
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz10 20/10/2011
Red phenolic
Meas...
Model-driven vs. Data-driven
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz11 20/10/2011
Red phenolic
Meas...
Data-driven Reflectance
• Example Surface
with Meso structure
• Results are „ABRDFs“
(apparent BRDFs [3])
3D COFORM STAR –...
Model-driven Reflectance
• Loss of Mesoscale depth impression…
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwa...
Data-driven Reflectance
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz14 20/10/2011
Texture Mesoscale
appr...
Form of Representation
Macroscopic scale
•3D shape
•Explicit representation
(e.g. polygon mesh)
Mesoscopic scale
•Individu...
Form of Representation
Macroscopic scale
•3D shape
•Explicit representation
(e.g. polygon mesh)
Mesoscopic scale
•Individu...
Form of Representation
Macroscopic scale
•3D shape
•Explicit representation
(e.g. polygon mesh)
Mesoscopic scale
•Individu...
ACQUISITION
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz18 20/10/2011
First use of BTF: CUReT Database
• 1996 – 1999 by Dana et al. [4]
• 61 materials
• 205 different view- and light direction...
University of Bonn BTF Database
• 2001 – 2003 Sarlette et al. [5]
• 6561 view and light directions
• 36-bit RGB images
• F...
University of Bonn Multiview Dome
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz21 20/10/2011
• 2004 – now...
First Capture of Complete Objects with BTF
• Furukawa et al. 2002 [6]
• Laser scanned geometry
• Separate BTF capture
 Ve...
First Capture of Complete Objects with BTF
• Furukawa et al. 2002 [6]
• Laser scanned geometry
• Separate BTF capture
 Ve...
Integrated Acquisition of Objects with BTF
• Müller et al. 2005 [7]
• Use University of Bonn Dome
• Dense sampling (22,801...
Integrated Acquisition of Objects with BTF
• Müller et al. 2005
Drawbacks:
 No radiometric calibration
• Misleading color...
Integrated HQ Acquisition
• Holroyd et al. 2010 [17]
• Integrated setup
• Geometry with Structured Light
• 42 view and lig...
Integrated HQ Acquisition
• Holroyd et al. 2010 [17]
• Integrated setup
• Geometry with Structured Light
• 42 view and lig...
Integrated HQ Acquisition with BTF
• Schwartz et al. 2011 [8]
• Use University of Bonn Dome
• Extended with projectors for...
Quality
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz29 20/10/2011
Faithfulness
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz30 20/10/2011
Photographic
picture
(tonemapped ...
Polynomial Texture Maps
• Malzbender et al. 2001 [9]: PTM
• Image-based, Sampling of Light (ωi)
 Incomplete appearance in...
Faithfulness
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz32 20/10/2011
Photographic
picture
(tonemapped ...
Multiview PTMs
• Gunawardane et al. 2009 [18]:
• PTMs from multiple viewpoints
 No macro scale
 interpolation of views v...
Full Light Transport with BTFs
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz34 20/10/2011
Full Light Transport with BTFs
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz35 20/10/2011
COMPRESSION, RENDERING AND
TRANSMISSION
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz36 20/10/2011
Datasizes
• Schwartz et al. 2011 [8]:
• Uncompressed BTF:
≈ 500 GB per object
• Not feasible even for
offline rendering…
3...
BTF Compression
• Fitting analytical models
• Wu et al. 2011 [15]: SPMM
• Model-driven…
• lost meso-structure
3D COFORM ST...
BTF Compression
• High degree of
redundancy in the BTF
• Perform statistical
data analysis
• Find low dimensional basis
• ...
Compression using Statistical Analysis
• Organization of the discrete BTF
• As matrix • As Tensor
3D COFORM STAR – VAST 20...
Full Matrix Factorization
• E.g. Liu et al. 2004 [14]: FMF
• Representation is compact
and realtime renderable [5]
3D COFO...
Decorrelated Full Matrix Factorization
• Gero Müller 2009 [13]: DFMF
• Insight from image compression (e.g. JPEG)
• Human ...
FMF Rendering
• Uncompressed: ≈ 500GB
• Compressed: ≈ 640MB
• 32 components
• Even fits on the GPU
• Random access to BTF
...
Interactive Inspection via GPU Rendering
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz44 20/10/2011
Streaming of BTF over the Internet
• Schwartz et al. 2011 [16]:
• Spatial components
≈ natural images
• Angular components...
Streaming of BTF over the Internet
3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz46 20/10/2011
0.87 MB
Fir...
Questions?
Learn more about
BTFs for Cultural
Heritag on
Wednesday [8]
and Thursday [16]
3D COFORM STAR – VAST 2011 Prato,...
References
[1] “A Data-Driven Reflectance Model”, Matusik W., Pfister H., Brand M. and McMillan L., ACM TOG 22, 3(2003),
7...
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Realistic Object Appearance using Bidirectional Texture Functions

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3D COFORM Star Day – VAST 2011, October 20 - Prato, Italy

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Realistic Object Appearance using Bidirectional Texture Functions

  1. 1. Institute of Computer Science II Computer Graphics Realistic Object Appearance using Bidirectional Texture Functions Christopher Schwartz, Reinhard Klein 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz1 20/10/2011
  2. 2. INTRODUCTION 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz2 20/10/2011
  3. 3. Object Appearance • Common presentation: Geometry (+ Texture) • … but is this sufficient? 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz3 20/10/2011 Geometry only With texture Correct appearance
  4. 4. Importance of Surface Appearance • Same shape, different materials • Different „look-and-feel“ • Important hints about the object • Misleading vs. better understanding 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz4 20/10/2011
  5. 5. Object Appearance • Impression of reflection of incident light • Influenced by features on different scales • Macroscopic • Mesoscopic • Microscopic • Viewpoint and Illumination dependent 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz5 20/10/2011
  6. 6. Form of Representation Macroscopic scale •3D shape •Explicit representation (e.g. polygon mesh) Mesoscopic scale •Individually resolved by human perception •Statistical representation not accurate •Explicit representation too costly Microscopic scale •Alignment of microscopic structures •Statistical representation (e.g. BRDF) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz6 20/10/2011
  7. 7. Bidirectional Reflectance Distribution Function • Opaque, uniform Materials • No texture! • Ratio of incident irradiance to outgoing radiance • Defined over local hemisphere • Depends on • Solid angle of light ωi • Solid angle of view ωo 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz7 20/10/2011
  8. 8. Bidirectional Reflectance Distribution Function • Example BRDF • sampled at discrete angles 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz8 20/10/2011 ωi ωo BRDF TabulatedExample: BRDF on Sphere Discrete sample positions on Hemisphere Specular reflection
  9. 9. Model-driven vs. Data-driven • Matusik et al. 2003 [1]: Measured BRDF ground-truth data • 100 real world materials • 1° resolution for view- and light directions • > 1,000,000 samples • Ngan et al. 2005 [2]: Experimental analysis of BRDF models 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz9 20/10/2011
  10. 10. Model-driven vs. Data-driven 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz10 20/10/2011 Red phenolic Measured distribution from [1] Fitted model (Cook-Torrance) from [2]
  11. 11. Model-driven vs. Data-driven 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz11 20/10/2011 Red phenolic Measured distribution from [1] Fitted model (Cook-Torrance) from [2]
  12. 12. Data-driven Reflectance • Example Surface with Meso structure • Results are „ABRDFs“ (apparent BRDFs [3]) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz12 20/10/2011 ωi ωo ωi ωo Specular reflection Retro-reflection Hard to fit with analytical model influence from neighborhood
  13. 13. Model-driven Reflectance • Loss of Mesoscale depth impression… 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz13 20/10/2011 Fitted analytical SVBRDF Photograph McAllister 2002 [10]
  14. 14. Data-driven Reflectance 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz14 20/10/2011 Texture Mesoscale approximated by Bump-mapping Data-Driven (BTF) Images taken from Müller et al. 2005 [7]
  15. 15. Form of Representation Macroscopic scale •3D shape •Explicit representation (e.g. polygon mesh) Mesoscopic scale •Individually resolved by human perception •Statistical representation not accurate •Explicit representation too costly Microscopic scale •Alignment of microscopic structures •Statistical representation (e.g. BRDF) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz15 20/10/2011
  16. 16. Form of Representation Macroscopic scale •3D shape •Explicit representation (e.g. polygon mesh) Mesoscopic scale •Individually resolved by human perception •Statistical representation not accurate •Explicit representation too costly Microscopic scale •Alignment of microscopic structures •Statistical representation (e.g. BRDF) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz16 20/10/2011 Data-driven: Image based
  17. 17. Form of Representation Macroscopic scale •3D shape •Explicit representation (e.g. polygon mesh) Mesoscopic scale •Individually resolved by human perception •Statistical representation not accurate •Explicit representation too costly Microscopic scale •Alignment of microscopic structures •Statistical representation (e.g. BRDF) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz17 20/10/2011 Bidirectional Texture Function
  18. 18. ACQUISITION 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz18 20/10/2011
  19. 19. First use of BTF: CUReT Database • 1996 – 1999 by Dana et al. [4] • 61 materials • 205 different view- and light directions • 24-bit RGB images  Manual placement of camera  BTF only partially measured 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz19 20/10/2011
  20. 20. University of Bonn BTF Database • 2001 – 2003 Sarlette et al. [5] • 6561 view and light directions • 36-bit RGB images • Fully automated • 12 hrs per acquisition 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz20 20/10/2011
  21. 21. University of Bonn Multiview Dome 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz21 20/10/2011 • 2004 – now by Sarlette et al. • 22,801 view and light directions • HDR images • Fully automated • No moving parts • 2hrs per acquisition
  22. 22. First Capture of Complete Objects with BTF • Furukawa et al. 2002 [6] • Laser scanned geometry • Separate BTF capture  Very sparse sampling  Alignment errors 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz22 20/10/2011 Photograph Rendering
  23. 23. First Capture of Complete Objects with BTF • Furukawa et al. 2002 [6] • Laser scanned geometry • Separate BTF capture  Very sparse sampling  Alignment errors 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz23 20/10/2011 Photograph Rendering
  24. 24. Integrated Acquisition of Objects with BTF • Müller et al. 2005 [7] • Use University of Bonn Dome • Dense sampling (22,801), 2hrs/acquisition • Measurements integrated in one setup • No registration necessary • Geometry via Shape-from-Silhouette 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz24 20/10/2011
  25. 25. Integrated Acquisition of Objects with BTF • Müller et al. 2005 Drawbacks:  No radiometric calibration • Misleading colors • Only LDR  Shape-from-Silhouette • Not automatable • Coarse geometry – Misleading Shape – Blur due to misalignment 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz25 20/10/2011 Example from Havemann et al. 2008 [12]
  26. 26. Integrated HQ Acquisition • Holroyd et al. 2010 [17] • Integrated setup • Geometry with Structured Light • 42 view and light directions • 5hrs per acquisition  Sparse sampling  Model-driven • Fit Cook-torrance BRDFs 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz26 20/10/2011 Photograph Rendering
  27. 27. Integrated HQ Acquisition • Holroyd et al. 2010 [17] • Integrated setup • Geometry with Structured Light • 42 view and light directions • 5hrs per acquisition  Sparse sampling  Model-driven • Fit Cook-torrance BRDFs 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz27 20/10/2011 Photograph Rendering
  28. 28. Integrated HQ Acquisition with BTF • Schwartz et al. 2011 [8] • Use University of Bonn Dome • Extended with projectors for Structured Light • integrated measurement • Rapid: 3.7 hrs per acquisition • Proper calibration and HDR • Geometry: Weinmann et al. 2011 [11] 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz28 20/10/2011 Visual Hull [7], [12] Laser Scan Proposed Method [11]
  29. 29. Quality 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz29 20/10/2011
  30. 30. Faithfulness 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz30 20/10/2011 Photographic picture (tonemapped HDR) BTF + Geometry Schwartz et al. 2011 [8] (tonemapped HDR)
  31. 31. Polynomial Texture Maps • Malzbender et al. 2001 [9]: PTM • Image-based, Sampling of Light (ωi)  Incomplete appearance information • View-dependent part of reflectance missing  For 3D Objects: only one fixed viewpoint 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz31 20/10/2011 PTM Texture
  32. 32. Faithfulness 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz32 20/10/2011 Photographic picture (tonemapped HDR) BTF + Geometry Schwartz et al. 2011 [8] (tonemapped HDR) Polynomial Texture Map Malzbender et al. 2001 [9] (Single view and LDR!)
  33. 33. Multiview PTMs • Gunawardane et al. 2009 [18]: • PTMs from multiple viewpoints  No macro scale  interpolation of views via optical flow  Limited amount of views • Combining multiple objects is hard • incorrect silhouttes, occlusion, shadows, etc. • Full light transport (i.e. path-tracing) not possible 33 20/10/2011 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz
  34. 34. Full Light Transport with BTFs 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz34 20/10/2011
  35. 35. Full Light Transport with BTFs 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz35 20/10/2011
  36. 36. COMPRESSION, RENDERING AND TRANSMISSION 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz36 20/10/2011
  37. 37. Datasizes • Schwartz et al. 2011 [8]: • Uncompressed BTF: ≈ 500 GB per object • Not feasible even for offline rendering… 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz37 20/10/2011
  38. 38. BTF Compression • Fitting analytical models • Wu et al. 2011 [15]: SPMM • Model-driven… • lost meso-structure 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz38 20/10/2011 BTF SPMM
  39. 39. BTF Compression • High degree of redundancy in the BTF • Perform statistical data analysis • Find low dimensional basis •  learn how to best describe the data 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz39 20/10/2011
  40. 40. Compression using Statistical Analysis • Organization of the discrete BTF • As matrix • As Tensor 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz40 20/10/2011 Angles ωi, ωo Pixels(x,y,color) Pixels (x,y) ωo Note: Color (or wavelength) can be additional dimension
  41. 41. Full Matrix Factorization • E.g. Liu et al. 2004 [14]: FMF • Representation is compact and realtime renderable [5] 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz41 20/10/2011 … ...            M           …V Angular components “Eigen-ABRDFs“           U … Spatial components “Eigen-Textures“SVD T M USV Importance
  42. 42. Decorrelated Full Matrix Factorization • Gero Müller 2009 [13]: DFMF • Insight from image compression (e.g. JPEG) • Human perception is more sensitive to variation in intensity than color • Also: chromacity in images exhibits less variation • Decorrelate the BTF data into luminance and chrominance – BTFRGB  BTFY BTFU BTFV • Use fewer components for chrominance channels U, V 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz42 20/10/2011
  43. 43. FMF Rendering • Uncompressed: ≈ 500GB • Compressed: ≈ 640MB • 32 components • Even fits on the GPU • Random access to BTF • Angular combination a = (ωi, ωo) • Pixel p = (x,y) 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz43 20/10/2011 components Angular component #1 Spatial component #1 Angular component #2 Spatial component #2 … … pixelangles BTF(a,p) = < , >
  44. 44. Interactive Inspection via GPU Rendering 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz44 20/10/2011
  45. 45. Streaming of BTF over the Internet • Schwartz et al. 2011 [16]: • Spatial components ≈ natural images • Angular components ≈ low frequency • Apply additional wavelet compression 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz45 20/10/2011 0.4bpp Wavelet 16bpp Reference
  46. 46. Streaming of BTF over the Internet 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz46 20/10/2011 0.87 MB First renderable version 1 MB 7 MB 46.4 MB Fully transmitted 534 GB Reference
  47. 47. Questions? Learn more about BTFs for Cultural Heritag on Wednesday [8] and Thursday [16] 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz47 20/10/2011
  48. 48. References [1] “A Data-Driven Reflectance Model”, Matusik W., Pfister H., Brand M. and McMillan L., ACM TOG 22, 3(2003), 759-769. [2] “Experimental Analysis of BRDF models”, Ngan A., Durand F. and Matusik W., Proceedings of EGSR, 2005, 117- 226. [3] „Image-based Rendering with Controllable Illumination“, Wong T., Heng P., Or S., and Ng W., Proceedings of EGWR, 1997, 13-22 [4] „Reflectance and Texture of Real-World Surfaces “, Dana K.J., van Ginneken B., Nayar S.K. and Koenderink J.J., Proceedings of CVPR, 1997, 151-157 [5] „Efficient and Realistic Visualization of Cloth“, Sattler M., Sarlette R. and Klein R., Proceedings of EGSR, 2003 [6]„Appearance based object modeling using texture database: acquisition, compression and rendering“, Furukawa R., Kawasaki H. Ikeuchi K. and Sakauchi M., Proceedings of EGRW 2002, 257-266 [7] „Rapid Synchronous Acquisition of Geometry and BTF for Cultural Heritage Artefacts“, Müller G., Bendels G.H. and Klein R., Proceedings of VAST, 2005 [8] „Integrated High-Quality Acquisition of Geometry and Appearance for Cultural Heritage”, Schwartz C., Weinmann W., Roland R. and Klein R., Proceedings of VAST, 2011 [9] „Polynomial Texture Maps“, Malzbender T., Gelb D. and Wolters H., Proceedings of SIGGRAPH, 2001 [10] „A Generalized Surface Appearance Representation For Computer Graphics“, McAllister D.K., PhD. Thesis, University of North Carolina at Chapel Hill, 2002 [11] „A Multi-Camera, Multi-Projector Super-Resolution Framework for Structured Light“, Weinmann M., Schwartz C., Ruiters R. and Klein R., Proceedings of 3DIMPVT, 2011, 397-404 [12] „The Presentation of Cultural Heritage Models in Epoch“, Havemann S., Settgast V., Fellner D., Willems G., Van Gool, L., Müller G., Schneider M. and Klein R., EPOCH Conference on Open Digital CH Systems, 2008 [13] „Data-Driven Methods for Compression and Editing of Spatially Varying Appearance“, Müller G., PhD. Thesis, University of Bonn, 2009 [14] „Synthesis and Rendering of Bidirectional Texture Functions on Arbitrary Surfaces“, Liu X., Hu Y., Zhang J. Tong X., Guo B. and Shum H.-Y., IEEE Transactions on Visualization and Computer Graphics 10 (3), 2004, 278-289 [15] „A Sparse Parametric Mixture Model for BTF Compression, Editing and Rendering“, Wu H., Dorsey J. and Rushmeier H., Computer Graphics Forum 30 (2), 2011, 465-473 [16] „WebGL-based Streaming and Presentation Framework for Bidirectional Texture Function“, Schwartz C., Ruiters R., Weinmann M. and Klein R., Proceedings of VAST, 2011 [17] „A coaxial optica scanner for synchronous acquisition of 3D geometry and surface reflectance“, Holroyd M., Lawrence J. and Zickler T., ACM Trans. Graph. 29 (4), 2010 [18] „Optimized Image Sampling for View and Light Interpolation“, Gunawardane P., Wang O., Scher S., Rickards I., Davis J. And Malzbender T., Proceedings of VAST, 2009 [19] „Principles and practices of robust, photography-based digital imaging techniques for museums.“, Mudge M., Schroer C., Ear G., Martinez K., Pagi H., Toler-Franklin C., Rusinkiewicz S., Palma G., Wochowiak M., Ashley M., Matthews N., Noble T. and Dellepiane M., Proceedings of VAST, 2010 3D COFORM STAR – VAST 2011 Prato, Italy – Christopher Schwartz48 20/10/2011

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