Abstract
We often have the experience of perceiving the colors and materials of objects in our environment effortlessly. But estimating the surface properties of objects is in fact a computationally hard problem for the visual system, because the light signal that reaches our eyes from surfaces in our environment depends not only on the reflectance of the surface, but also on the illumination impinging on the surface. Statistical regularities about surfaces and illuminants, learned through interacting with our environment and through social communication, may contribute to our ability to compensate for changes in illumination when estimating object color. These statistical regularities may be learned at different timescales from species evolution to individual development to something akin to temporary adaptation. For instance, the typical colors of objects, as well as color categories -- both learned through experience -- may anchor color perception under illumination changes. More short-term learning may also stabilize color perception under more abrupt changes in the environment. In this talk, I will present research on the influence of long-term and short-term color knowledge on color appearance, and link this with color constancy in a probabilistic estimation framework. I will end by discussing ongoing research to push the study of color constancy to more realistic scenes and tasks.