Identifying regions that carry the best information about global facial configurations

Regions of the face are not equally important in conveying information about configural change. The bubbles spatial occlusion technique has proved to be a good method for revealing which areas carry diagnostic facial information for different perceptual categorization tasks. We have applied it here within a performance-driven mimicry system implemented using a computer-generated model of the face designed to automatically retarget the behavior of one face onto another face. Our bubbles technique, mapping an occluded face into a PCA model of the same face, revealed the areas around and including the mouth and eyebrows as the most important for facial image reconstruction. These regions overlapped with but interestingly were not identical to areas of maximum pixel-value variance. Here we show a system that is indifferent to stimulus content and uses the correlation between vectors in face space as a criterion, rather than just pixel-value correlation, identifies the eyebrows and mouth as important regions. This implies that the importance of the eyebrows and the mouth in dynamic face perception may depend not on the information content of the features per se but on the degree to which these regions of the face provide information about the global form of the face.