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Specular Highlights. Full Surface Specularity. Uniform Background. Cue Promotion. Illuminant Estimate. Scene. Dynamic Re-Weighting. #1255 S URFACE C OLOR AND S PECULARITY : T ESTING THE D’Z MURA -L ENNIE -L EE M ODEL - PowerPoint PPT PresentationTRANSCRIPT
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#1255 SURFACE COLOR AND SPECULARITY: TESTING THE D’ZMURA-LENNIE-LEE MODELJ. N. YANG & L. T. MALONEY, Department of Psychology and Center for Neural Science, New York University
ILLUMINANT CUE COMBINATION
UniformBackground
SpecularHighlights
Full SurfaceSpecularity
Dynamic Re-Weighting
Scene
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Cue Promotion3. PERTURBATION METHOD
Our rendered scenes contain many potential illuminant cues,all signaling exactly the same information about the illuminant.In order to determine the influence of cues based on specularity, we need to perturb the specularity cues so that they signal slightly discrepant information concerning the illuminant.
base D65 perturbed
The first and third scene above are a single-matte scene illuminated under two different illuminants. The middle scene is perturbed: all illuminant cues except specularity signal D65 (the base illuminant) while all specularity cues signal A.
We measure the observer’s achromatic setting in all three scenes.
If the observer’s achromatic setting for the perturbed scene is identical to that for thebase D65 scene, then the perturbation had no effect. The observer is not influenced bythe specular information.
If the observer’s achromatic setting for the perturbed scene is identical to that for thetarget A scene, then only specularity influences the observer’s judgment. Perturbingspecularity is equivalent to changing the illuminant on the scene.
We expect that the achromatic setting for the perturbed scene will fall somewhere between the achromatic settings for the base scene D65 and the achromatic settingfor the target scene A, and we use this to quantify the influence of the cue.
The roles of the two illuminants can be reversed with A as base, D65 as target.
target A
Illuminant A
Illuminant D65
Specularity cues perturbed ...
There are currently two kinds of specularity-based algorithms for estimating illuminant chromaticity.
In the first method, we use the chromaticity of isolated specular highlights as an estimate of illuminant chromaticity.
This specular highlight cue is available if a visual system can identify neutral specular highlights in scenes.
The illuminant chromaticity estimate based on this specular highlight cue can be contaminated by the color of the matte(non-specular) component of a surface.
SPECULAR HIGHLIGHT
JNYTarget A
Perturbed Illuminant D65 (matte) Illuminant A (specular)
Base D65
Illuminant A
Illuminant D65
Lee (1986) and D’Zmura & Lennie (1986) independentlyproposed methods for removing the ‘matte’ contamination.
Both methods require that there be two or more surfaces with distinct matte components with some specularity in the scene.The scene to the right satisfies this condition. The scene above itdoes not. The apples all share the same matte component.
We compare surface color perception in scenes where specularobjects have a single common matte component (Single-Matte Scenes)and where they have multiple distinct matte components(Multi-Matte Scenes).
D’ZMURA-LENNIE-LEE CUE
Stimulus Characteristics:
Observers viewed simulated (rendered) binocular scenes comprising a flat background and 11 spheres.
All surfaces were Matte-Specular (Shafer, 1985) with mattecomponent matched to specific chips taken from the Nickerson-Munsell collection.
In the Single-Matte Scenes, all sphere surfaces shared a singlematte component, in Multi-Matte Scenes they had 11 distinct mattecomponents.
Scenes were rendered under either of two reference illuminants, A and D65 ( Wyszecki & Stiles, 1982).
Task: achromatic matching.
A D65
Single-Matte
Multi-Matte
Apparatus: Observers viewed stimuli in a computer-controlled Wheatstone stereoscope.
REFERENCES
D’Zmura, M. & Lennie, P. (1986), Mechanisms of color constancy. JOSA A, 3, 1662-1672.
Landy, M. S., Maloney, L. T., Johnston, E. J. & Young, M. (1995), Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Research, 35, 389-412.
Lee, H.-C. (1986), Method for computing the scene illuminant chromaticity from specular highlights. JOSA A, 3, 1694-1699.
Maloney, L. T. (1999), Physics-based models of surface color perception. In Gegenfurtner, K. R. & Sharpe, L. T. [Eds] (1999), Color Vision: From Genes to Perception. Cambridge, UK: Cambridge University Press, 387-418.
Maloney, L. T. & Yang, J. N. (in press), The illumination estimation hypothesis. In Mausfeld, R. & Heyer, D. [Eds] (in press) Colour Vision: From Light to Object. Oxford: Oxford University Press.
Yang, J. N., Maloney, L. T. & Landy, M. S. (1999), Analysis of illuminant cues in simulated scenes viewed binocularly. IOVS, 40.
Many computational models of surface color perception share a common structure:
1. estimate the chromaticity of the illuminant,
2. correct surface colors for the estimated illuminant chromaticity.
The algorithms differ mainly in the physical cues to the illuminant they employ.
There are many possible cues to the illuminant (Maloney, 1999), not all of which are present in every scene. We treat illuminant estimation as a cue combination problem and seek to determine which cues to the illuminant are used in particular scenes.
Last year (Yang, Maloney & Landy, 1999) we reported that information about the illuminant conveyed by surface specularity influenced judgments of color appearance.
5. RESULTS
[I]n our observations with the sense of vision, we always start
out by forming a judgment aboutthe colors of bodies, eliminatingthe differences of illumination bywhich a body is revealed to us.
-- von Helmholtz
1. SPECULAR CUES
2. EXPERIMENTAL DESIGN
4. EXPERIMENTAL CONDITIONS
Surface color appearance is affected by the chromaticity of the specular componentof surfaces in some scenes, under some illuminants (Yang, Maloney & Landy, 1999).
We measured achromatic matching performance in two classes of scenes containing evident specular cues to the illuminant: Single-Matte and Multi-Matte.
The D’Zmura-Lennie-Lee specularity cue is available in the Multi-Matte scenes but is weak or absent in the Single-Matte scenes.
Specularity had no influence on achromatic performance in the Multi-Matte scenes.
We conclude that the visual system is not making use of the D’Zmura-Lennie-Lee specular cue in these scenes.
6. CONCLUSIONS
SPECULAR HIGHLIGHT CUE
Single-Matte Scene
Multi-Matte Scene
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The influence of the specularity cues can be quantifiedas the ratio of the length of the solid vector (the effectof perturbation) to the length of the dotted line connectingthe base and target conditions (the effect of changing theilluminant):
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