Gender Recognition of Human Faces Using Color

A continuing question in the object recognition literature is whether surface properties play a role in visual representation and recognition. Here, we examined the use of color as a cue in facial gender recognition by applying a version of reverse correlation to face categorization in CIE L(*)a(*)b(*) color space. We found that observers exploited color information to classify ambiguous signals embedded in chromatic noise. The method also allowed us to identify the specific spatial locations and the components of color used by observers. Although the color patterns found with human observers did not accurately mirror objective natural color differences, they suggest sensitivity to the contrast between the main features and the rest of the face. Overall, the results provide evidence that observers encode and can use the local color properties of faces, in particular, in tasks in which color provides diagnostic information and the availability of other cues is reduced.