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Effect of Test Patch Location on Color Appearance, in the Context of 3D Objects

Effect of Test Patch Location on Color Appearance, in the Context of 3D Objects. Bei Xiao and David H.Brainard University of Pennsylvania. What Color is the Mug?. Most Appearance Studies Consider Flat Uniform Patches. A Complex Pattern of Light is Reflected from 3D Objects. Highlight.

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Effect of Test Patch Location on Color Appearance, in the Context of 3D Objects

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  1. Effect of Test Patch Location on Color Appearance, in the Context of 3D Objects Bei Xiao and David H.Brainard University of Pennsylvania

  2. What Color is the Mug?

  3. Most Appearance Studies Consider Flat Uniform Patches

  4. A Complex Pattern of Light is Reflected from 3D Objects Highlight Inter-reflection Inter-reflection

  5. Surface Gloss Increases the Variation of Reflected Light

  6. Questions How do people perceive the color of different parts of an object? How do material properties of the object affect color perception?

  7. Task: Asymmetric Color Matching Test Match

  8. Task: Asymmetric Color Matching Adjusting! Test Match

  9. Task: Asymmetric Color Matching Adjusting! Test Match

  10. Task: Asymmetric Color Matching Adjusting! Test Match

  11. Task: Asymmetric Color Matching Adjusting! Test Match

  12. Task: Asymmetric Color Matching Adjusting! Test Match

  13. Task: Asymmetric Color Matching Done! Test Match

  14. Rendering Methods Images are rendered wavelength by wavelength using customized Matlab software (RenderToolbox). The underlying renderer is Radiance. RenderToolbox is available at www.rendertoolbox.org.

  15. Ward Model of Surface Reflection Specular Component (material properties) Diffuse Component (body color)

  16. Experimental Variables: Location, Material, Color Location Material Color

  17. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  18. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  19. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  20. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  21. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  22. Results: Pictorial Representation Test Up Test Bottom Mean Up Mean Bottom Match Up Match Bottom

  23. Preliminary Conclusions Changing test patch location of an object has a small effect on color perception of the patch. This is not predicted by the average of the light reflected from the patch. Effect of surface material properties on color perception of the patch is also small.

  24. Quantitative Data Representation test mean Xiao, B. and Brainard, D.H. (under review) Visual Neuroscience

  25. Transformed Data Representation test mean

  26. Transformed Data Representation test mean match

  27. Transformed Data Representation test mean match

  28. Transformed Data Representation test mean match

  29. Transformed Data Representation test mean match

  30. Transformed Data Representation test mean match

  31. Soccer Ball Experiment, More Data

  32. Location Effect Index (LEI) up test Vt Vm mean bottom match For each material condition:LEI = [ |Vm| / |Vt| ]

  33. LEI Histograms Corrected mean: Purple = 0.09 Yellow-green = 0.13

  34. Material Influence Index (MII) glossy test Vt Vm mean matte match For each mach: MII = [ |Vm| / |Vt| ]

  35. MII Histograms Corrected mean: Purple = 0.17 Yellow-green = 0.13

  36. Conclusions We’re interested in the color appearance of 3D objects in rich scenes. Effect of location is small in comparison with the mean prediction. This suggests color appearance is stable across different parts of an object. Surface gloss has a small effect on color perception of the test patch on 3D objects when the diffuse component is constant. Matches are not predicted by the average of the light reflected across the image of the object.

  37. Acknowledgement Prof. David H. Brainard Dan Lichtman Ah Rim Shin Lu Yin Dr. Sarah Allred Dr. Robyn Oliver Chris Broussard Prof. James Hillis

  38. Implications For Models Image-statistics: Use image mean, skewness, percentiles to estimate diffuse reflectance (body color). Inverse-optics: estimating geometry of the light source and use the estimated geometry to infer diffuse reflectance.

  39. Design: Test Patch Location Effect

  40. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  41. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  42. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  43. CIELAB Representation of Test Stimuli

  44. LEI Histograms, Compared with Residuals

  45. Material Influence Index (LEI)

  46. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  47. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  48. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

  49. Results: Pictorial Representation Test Up Test Bottom Match Up Match Bottom Mean Up Mean Bottom

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