Constancy, Categories and Bayes: A New Approach to Representational Theories of Color Constancy

Philosophers have long sought to explain perceptual constancy—the fact that objects appear to remain the same color, size and shape despite changes in the illumination condition, perspective and the relative distance—in terms of a mechanism that actively categorizes variable stimuli under the same pre-formed conceptual categories. Contemporary representationalists, on the other hand, explain perceptual constancy in terms of a modular mechanism that automatically discounts variation in the visual field to represent the stable properties of objects. In this paper I argue that while the former view is unmotivated by empirical evidence, the later fails to account for inter- and intra-personal variability, the influence of expectations on constancy, and the systematic and normal failures of color constancy. A Bayesian approach that builds on the representational tradition in psychology solves both problems.