Sex Classiication Is Better with Three-dimensional Head Structure than with Image Intensity Information

Sex classiication of faces 2 Abstract 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 graylevel image 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 diierences between the three-dimensional structure of male and female heads and between male and female graylevel image maps. In a series of simulations, we compared the quality of the information available in the three-dimensional head versus graylevel image data for predicting the sex of the face. The results indicated that the three-dimensional head data supported more accurate sex classiication than the graylevel image 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.