Color and material perception: Achievements and challenges

Maloney, Laurence T.; Brainard, David H.

doi:10.1167/10.9.19

Cited by 68 publications

(25 citation statements)

References 76 publications

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“…It tells us that a single set of principles can be used to provide a unified account of constancy across this range of scenes, and suggests that the same ideas may continue to work as the field moves to yet richer viewing conditions (for an overview of some recent work, see Maloney & Brainard, 2010). …”

Section: Discussionmentioning

confidence: 99%

Surface color perception and equivalent illumination models

2011

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Vision provides information about the properties and identity of objects. The ease with which we make such judgments belies the difficulty of the information-processing task that accomplishes it. In the case of object color, retinal information about object reflectance is confounded with information about the illumination as well as about the object’s shape and pose. Because of these factors, there is no obvious rule that allows transformation of the retinal images of an object to a color representation that depends primarily on the object’s surface reflectance properties. Despite the difficulty of this task, however, under many circumstances object color appearance is remarkably stable across scenes in which the object is viewed. Here we review experiments and theory that aim to understand how the visual system stabilizes the color appearance of object surfaces. Our emphasis is on a class of models derived from explicit analysis of the computational problem of estimating the physical properties of illuminants and surfaces from the information available in the retinal image and experiments that test these models. We argue that this approach has considerable promise for allowing generalization from simplified laboratory experiments to richer scenes that more closely approximate natural viewing.

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Section: Discussionmentioning

confidence: 99%

Surface color perception and equivalent illumination models

2011

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“…Our visual system is able to extract information about these surface reflectance properties from the retinal image, and the resultant perception of surface quality plays an important role in the identification of materials and the recognition of objects (Hunter and Harold, 1987;Adelson, 2001;Maloney and Brainard, 2010). Attempts to understand the neural processing underlying the perception of surface qualities have emerged in recent years (Arcizet et al, 2008;Köteles et al, 2008), and functional imaging studies in human subjects have shown that the ventral higher visual areas are activated when subjects attend to or discriminate materials Goodale, 2007, 2011;Cant et al, 2009;Cavina-Pratesi et al, 2010;Hiramatsu et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Neural Selectivity and Representation of Gloss in the Monkey Inferior Temporal Cortex

Nishio

Goda²,

Komatsu³

2012

Journal of Neuroscience

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When we view an object, its appearance depends in large part on specific surface reflectance properties; among these is surface gloss, which provides important information about the material composition of the object and the fine structure of its surface. To study how gloss is represented in the visual cortical areas related to object recognition, we examined the responses of neurons in the inferior temporal (IT) cortex of the macaque monkey to a set of object images exhibiting various combinations of specular reflection, diffuse reflection, and roughness, which are important physical parameters of surface gloss. We found that there are neurons in the lower bank of the superior temporal sulcus that selectively respond to specific gloss. This neuronal selectivity was largely maintained when the shape or illumination of the object was modified and perceived glossiness was unchanged. By contrast, neural responses were significantly altered when the pixels of the images were randomly rearranged, and perceived glossiness was dramatically changed. The stimulus preference of these neurons differed from cell to cell, and, as a population, they systematically represented a variety of surface glosses. We conclude that, within the visual cortex, there are mechanisms operating to integrate local image features and extract information about surface gloss and that this information is systematically represented in the IT cortex, an area playing an important role in object recognition.

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“…In particular, colors of materials strongly influence on the perception of material textures [2]. Therefore, we believe that it is significant to recommend colors suitable for material textures.…”

Section: Introductionmentioning

confidence: 99%

A method to propose color associated with onomatopoeia based on sound symbolism

Iiba

Shiga

Sakamoto

2012

The 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced In

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Color of materials influence on texture perceptions. Therefore, it is significant to recommend colors suitable for tactile sensations. In Japanese, tactile experiences are easily and frequently expressed by onomatopoeias such as "sara-sara" and "huwa-huwa". In this paper, we propose a system which recommends colors appropriate for tactile sensations associated with onomatopoeias based on Japanese sound symbolism. Our system estimates tactile images evoked by an input onomatopoeia quantitatively and calculates the similarities between the onomatopoeia and colors, whose images were respectively evaluated by SD scales in the psychological experiments. We conducted an experiment in order to confirm the validity of our system. Results indicate that our system succeeded in selecting cognitively plausible colors to represent tactile images of onomatopoeias. Our method makes it possible to develop a system which recommends materials with tactile sensations and colors desired by users via onomatopoeias.

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Color and material perception: Achievements and challenges

Cited by 68 publications

References 76 publications

Surface color perception and equivalent illumination models

Surface color perception and equivalent illumination models

Neural Selectivity and Representation of Gloss in the Monkey Inferior Temporal Cortex

A method to propose color associated with onomatopoeia based on sound symbolism

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