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A Probabilistic Model of the Categorical Association Between Colors

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In this paper we describe a non-parametric probabilistic model that can be used to encode relationships in color naming datasets. This model can be used with datasets with any number of color terms and expressions, as well as terms from multiple languages. Because the model is based on probability theory, we can use classic statistics to compute features of interest to color scientists. In particular, we show that the uniqueness of a color name (color saliency) can be captured using the entropy of the probability distribution. We demonstrate this approach by applying this model to two different datasets: the multi-lingual World Color Survey (WCS), and a database collected via the web by Dolores Labs. We demonstrate how saliency clusters similarly named colors for both datasets, and compare our WCS results to those of Kay and his colleagues. We compare the two datasets to each other by converting them to a common colorspace (IPT).
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Document Type: Research Article

Publication date: January 1, 2008

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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