Categorical color constancy for simulated surfaces

Abstract

Color constancy is the ability to perceive constant surface colors under varying lighting conditions. Color constancy has traditionally been investigated with asymmetric matching, where stimuli are matched over two different contexts, or with achromatic settings, where a stimulus is made to appear gray. These methods deliver accurate information on the transformations of single points of color space under illuminant changes, but can be cumbersome and unintuitive for observers. Color naming is a fast and intuitive alternative to matching, allowing data collection from a large portion of color space. We asked observers to name the colors of 469 Munsell surfaces with known reflectance spectra simulated under five different illuminants. Observers were generally as consistent in naming the colors of surfaces under different illuminants as they were naming the colors of the same surfaces over time. The transformations in category boundaries caused by illuminant changes were generally small and could be explained well with simple linear models. Finally, an analysis of the pattern of naming consistency across color space revealed that largely the same hues were named consistently across illuminants and across observers even after correcting for category size effects. This indicates a possible relationship between perceptual color constancy and the ability to consistently communicate colors.