Color Name Models
Our ability to reliably name colors provides a link between visual perception and symbolic cognition. In this project, we investigate how a statistical model of color naming can enable user interfaces to meaningfully mimic this link and support enhanced interactions.
We construct a probabilistic model of color naming from a large, unconstrained set of human color name judgments. This model can be used to map between colors and names and to define metrics for color saliency (how reliably a color is named) and color name distance (the similarity between colors based on naming patterns).
This model can enable enhanced user interfaces. Demo applications linked below include a color dictionary & thesaurus, evaluation aids for color palette design and name-based pixel selection methods for image editing.
applications
Color Dictionary & ThesaurusColor Palette Analyzer
Named-Based Image Editing Pixel Selector (Requires HTML Canvas Support)
Saliency Map of LAB Color Space (Requires SVG Support)