A survey of skin-color modeling and detection methods

Colorization, the task of coloring a grayscale image or video, involves assigning from the single dimension of intensity or luminance a quantity that varies in three dimensions, such as red, green, and blue channels. Mapping between intensity and color is, therefore, not unique, and colorization is ambiguous in nature and requires some amount of human interaction or external information. A computationally simple, yet effective, approach of colorization is presented in this paper. The method is fast and it can be conveniently used "on the fly," permitting the user to interactively get the desired results promptly after providing a reduced set of chrominance scribbles. Based on the concepts of luminance-weighted chrominance blending and fast intrinsic distance computations, high-quality colorization results for still images and video are obtained at a fraction of the complexity and computational cost of previously reported techniques. Possible extensions of the algorithm introduced here included the capability of changing the colors of an existing color image or video, as well as changing the underlying luminance, and many other special effects demonstrated here.

/pdf/fast-image-and-video-colorization-using-chrominance-blending-251n3pz2x8.pdf

Fast image and video colorization using chrominance blending

Color preference is an important aspect of visual experience, but little is known about why people in general like some colors more than others. Previous research suggested explanations based on biological adaptations [Hurlbert AC, Ling YL (2007) Curr Biol 17:623–625] and color-emotions [Ou L-C, Luo MR, Woodcock A, Wright A (2004) Color Res Appl 29:381–389]. In this article we articulate an ecological valence theory in which color preferences arise from people’s average affective responses to color-associated objects. An empirical test provides strong support for this theory: People like colors strongly associated with objects they like (e.g., blues with clear skies and clean water) and dislike colors strongly associated with objects they dislike (e.g., browns with feces and rotten food). Relative to alternative theories, the ecological valence theory both fits the data better (even with fewer free parameters) and provides a more plausible, comprehensive causal explanation of color preferences.

https://www.pnas.org/content/pnas/107/19/8877.full.pdf

An ecological valence theory of human color preference

http://www.filosofia.unimi.it/zucchi/NuoviFile/ColorCategoriesCulturalRelativity.pdf

Color categories: Evidence for the cultural relativity hypothesis

The existence of cross-linguistic universals in color naming is currently contested. Early empirical studies, based principally on languages of industrialized societies, suggested that all languages may draw on a universally shared repertoire of color categories. Recent work, in contrast, based on languages from nonindustrialized societies, has suggested that color categories may not be universal. No comprehensive objective tests have yet been conducted to resolve this issue. We conduct such tests on color naming data from languages of both industrialized and nonindustrialized societies and show that strong universal tendencies in color naming exist across both sorts of language.

/pdf/resolving-the-question-of-color-naming-universals-1lkaujpj1h.pdf

William R. Mathew

Papers

Color as a Science