The Role of Shape and Texture Information in Sex Classiication

The sex of a face is perhaps its most salient feature. A principal components analysis (PCA) was applied separately to the three-dimensional structure and texture data from laser-scanned human heads. Individual components from both analyses captured information related to the sex of the face. Notably, single projection coeecients characterized complex structural diierences between three-dimensional male and female heads and between male and female texture maps. In a series of simulations, we compared the quality of the information available in the head versus texture data for predicting in the sex of the face. The results indicated that the three-dimensional structural data supported more accurate sex classiication than the texture data, across a range of PCA-compressed (dimensionality-reduced) representations of the heads. This kind of dual face representation can give insight into the nature of the information available to humans for categorizing and remembering faces. The order of the rst two authors is arbitrary. Many thanks are due to Harald Volz for work on stimulus processing and display tools and to Guy Wallis for useful advice on the project. A.O. gratefully acknowledges the support of the Alexander von Humboldt Foundation and the hospitality of the Max Planck Institut f ur biologische Kybernetik, T ubingen, Germany.