A computational shape-based model of anger and sadness justifies a configural representation of faces

Abstract

Research suggests that configural cues (second-order relations) play a major role in the representation and classification of face images; making faces a “special” class of objects, since object recognition seems to use different encoding mechanisms. It is less clear, however, how this representation emerges and whether this representation is also used in the recognition of facial expressions of emotion. In this paper, we show how configural cues emerge naturally from a classical analysis of shape in the recognition of anger and sadness. In particular our results suggest that at least two of the dimensions of the computational (cognitive) space of facial expressions of emotion correspond to pure configural changes. The first of these dimensions measures the distance between the eyebrows and the mouth, while the second is concerned with the height–width ratio of the face. Under this proposed model, becoming a face “expert” would mean to move from the generic shape representation to that based on configural cues. These results suggest that the recognition of facial expressions of emotion shares this expertise property with the other processes of face processing.