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A unified account of perceptual layering and surface appearance in terms of gamut relativity.

Vladusich T, McDonnell MD - PLoS ONE (2014)

Bottom Line: Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye.Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking.Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations.

View Article: PubMed Central - PubMed

Affiliation: Institute for Telecommunications Research, University of South Australia, Mawson Lakes, 5095, Australia; Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA, United States of America.

ABSTRACT
When we look at the world--or a graphical depiction of the world--we perceive surface materials (e.g. a ceramic black and white checkerboard) independently of variations in illumination (e.g. shading or shadow) and atmospheric media (e.g. clouds or smoke). Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye. One way to understand how these percepts arise is to assume that the visual system parses patterns of light into layered perceptual representations of surfaces, illumination and atmospheric media, one seen through another. Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking. Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations. The model (a) qualitatively explains striking effects of perceptual transparency, figure-ground separation and lightness, (b) quantitatively accounts for the role of stimulus- and task-driven constraints on perceptual matching performance, and (c) unifies two prominent theoretical frameworks for understanding surface appearance. The model thereby provides novel insights into the remarkable capacity of the human visual system to represent and identify surface materials, illumination and atmospheric media, which can be exploited in computer graphics applications.

No MeSH data available.


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Two dramatic effects of perceptual layering and surface appearance.(A) Adelson checkerboard image [1] adapted from http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html under the Creative Commons Attribution License: Checks labelled A and B (depicted as appearing in bright and dim illumination) have the same point-to-point luminance but check B appears light gray and check A dark gray. Checks B and D are seen through a ‘transparent shadow layer’, whereas checks A and C are seen in ‘plain view’ (without an accompanying transparent layer). Variations in illumination intensity level produce multiplicative changes in the luminance values depicted as being reflected from the checks in bright and dim illumination. (B) Anderson-Winawer effect reprinted from [12]: Chess pieces in the upper and lower rows have the same point-to-point luminance but appear white and black, respectively. The white pieces are seen through a blackish transparent ‘atmosphere’ whose transparency varies across space, while the black pieces are seen through a transparent whitish atmosphere. Variations in atmospheric transmittance levels produce additive changes in the luminance values depicted as being reflected from the black and white chess pieces. This article develops a model that aims to quantitatively predict surface lightness through transparent layers, irrespective of the physical source of the transparent layer.
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pone-0113159-g001: Two dramatic effects of perceptual layering and surface appearance.(A) Adelson checkerboard image [1] adapted from http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html under the Creative Commons Attribution License: Checks labelled A and B (depicted as appearing in bright and dim illumination) have the same point-to-point luminance but check B appears light gray and check A dark gray. Checks B and D are seen through a ‘transparent shadow layer’, whereas checks A and C are seen in ‘plain view’ (without an accompanying transparent layer). Variations in illumination intensity level produce multiplicative changes in the luminance values depicted as being reflected from the checks in bright and dim illumination. (B) Anderson-Winawer effect reprinted from [12]: Chess pieces in the upper and lower rows have the same point-to-point luminance but appear white and black, respectively. The white pieces are seen through a blackish transparent ‘atmosphere’ whose transparency varies across space, while the black pieces are seen through a transparent whitish atmosphere. Variations in atmospheric transmittance levels produce additive changes in the luminance values depicted as being reflected from the black and white chess pieces. This article develops a model that aims to quantitatively predict surface lightness through transparent layers, irrespective of the physical source of the transparent layer.

Mentions: Models of physical light transport attempt to capture the immensely complicated ways in which physical surfaces and atmospheric media reflect, refract, scatter and transmit light [3]–[5]. The net result is that the light patterns reaching the eye from a rendered image consist of a mixture of physically modelled causes. Light ‘reflected’ from a rendered transparent surface using a standard α-blending model, for example, is combined with light ‘transmitted’ through the surface from the background [6]. Thus, even simple diffuse shading and/or blending models produce images that the human visual system parses into layered perceptual representations, one seen through another, as illustrated by the striking perceptual effects shown in Fig. 1. How the human visual system parses such images into separate material, illumination and atmospheric layers remains a challenging problem in both human vision science and computer vision science.


A unified account of perceptual layering and surface appearance in terms of gamut relativity.

Vladusich T, McDonnell MD - PLoS ONE (2014)

Two dramatic effects of perceptual layering and surface appearance.(A) Adelson checkerboard image [1] adapted from http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html under the Creative Commons Attribution License: Checks labelled A and B (depicted as appearing in bright and dim illumination) have the same point-to-point luminance but check B appears light gray and check A dark gray. Checks B and D are seen through a ‘transparent shadow layer’, whereas checks A and C are seen in ‘plain view’ (without an accompanying transparent layer). Variations in illumination intensity level produce multiplicative changes in the luminance values depicted as being reflected from the checks in bright and dim illumination. (B) Anderson-Winawer effect reprinted from [12]: Chess pieces in the upper and lower rows have the same point-to-point luminance but appear white and black, respectively. The white pieces are seen through a blackish transparent ‘atmosphere’ whose transparency varies across space, while the black pieces are seen through a transparent whitish atmosphere. Variations in atmospheric transmittance levels produce additive changes in the luminance values depicted as being reflected from the black and white chess pieces. This article develops a model that aims to quantitatively predict surface lightness through transparent layers, irrespective of the physical source of the transparent layer.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4234682&req=5

pone-0113159-g001: Two dramatic effects of perceptual layering and surface appearance.(A) Adelson checkerboard image [1] adapted from http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html under the Creative Commons Attribution License: Checks labelled A and B (depicted as appearing in bright and dim illumination) have the same point-to-point luminance but check B appears light gray and check A dark gray. Checks B and D are seen through a ‘transparent shadow layer’, whereas checks A and C are seen in ‘plain view’ (without an accompanying transparent layer). Variations in illumination intensity level produce multiplicative changes in the luminance values depicted as being reflected from the checks in bright and dim illumination. (B) Anderson-Winawer effect reprinted from [12]: Chess pieces in the upper and lower rows have the same point-to-point luminance but appear white and black, respectively. The white pieces are seen through a blackish transparent ‘atmosphere’ whose transparency varies across space, while the black pieces are seen through a transparent whitish atmosphere. Variations in atmospheric transmittance levels produce additive changes in the luminance values depicted as being reflected from the black and white chess pieces. This article develops a model that aims to quantitatively predict surface lightness through transparent layers, irrespective of the physical source of the transparent layer.
Mentions: Models of physical light transport attempt to capture the immensely complicated ways in which physical surfaces and atmospheric media reflect, refract, scatter and transmit light [3]–[5]. The net result is that the light patterns reaching the eye from a rendered image consist of a mixture of physically modelled causes. Light ‘reflected’ from a rendered transparent surface using a standard α-blending model, for example, is combined with light ‘transmitted’ through the surface from the background [6]. Thus, even simple diffuse shading and/or blending models produce images that the human visual system parses into layered perceptual representations, one seen through another, as illustrated by the striking perceptual effects shown in Fig. 1. How the human visual system parses such images into separate material, illumination and atmospheric layers remains a challenging problem in both human vision science and computer vision science.

Bottom Line: Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye.Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking.Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations.

View Article: PubMed Central - PubMed

Affiliation: Institute for Telecommunications Research, University of South Australia, Mawson Lakes, 5095, Australia; Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA, United States of America.

ABSTRACT
When we look at the world--or a graphical depiction of the world--we perceive surface materials (e.g. a ceramic black and white checkerboard) independently of variations in illumination (e.g. shading or shadow) and atmospheric media (e.g. clouds or smoke). Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye. One way to understand how these percepts arise is to assume that the visual system parses patterns of light into layered perceptual representations of surfaces, illumination and atmospheric media, one seen through another. Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking. Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations. The model (a) qualitatively explains striking effects of perceptual transparency, figure-ground separation and lightness, (b) quantitatively accounts for the role of stimulus- and task-driven constraints on perceptual matching performance, and (c) unifies two prominent theoretical frameworks for understanding surface appearance. The model thereby provides novel insights into the remarkable capacity of the human visual system to represent and identify surface materials, illumination and atmospheric media, which can be exploited in computer graphics applications.

No MeSH data available.


Related in: MedlinePlus