Prof. Dr. Stefan R. Schweinberger, DFG Research Unit Person Perception, Friedrich Schiller University, Jena

Abstract:

Face recognition is often believed to be based on some sort of ‘‘configural’’ or ‘‘holistic’’ processing. Although these terms are not always defined clearly in the literature, an influential hypothesis is that the recognition of individual faces depends, to a considerable extent, on shape in terms of metric distances between features (so-called second-order configural information). Here I will argue that this idea is not easily reconciled with a number of empirical findings. First, I will show evidence that familiar faces are well recognized even when idiosyncratic shape has been eliminated by shape normalization – suggesting a strong role of texture/surface reflectance for recognition. I will then present several face learning experiments that examined the impact of selective photorealistic caricaturing of either shape or texture information on face recognition and its neuronal correlates in event-related brain potentials. These experiments also confirm that shape is of little importance for the recognition of familiar faces, whereas shape enhancement was shown to facilitate the encoding of new faces. Moreover, distinctive texture/reflectance information was found to be particularly important for the recognition of learned faces. Overall, the present experiments underline the importance of face familiarity for mental representations of faces. Crucially, the configural processing hypothesis in its traditional form does not well account for the findings reported, and thus should be reconsidered.