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Vortrag

Investigating face recognition with voices and face morphs

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83840

Bülthoff,  I
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Bülthoff, I. (2006). Investigating face recognition with voices and face morphs. Talk presented at Face Mini-Symposium: Georg-August-Universität Göttingen, Zentrum für Neurobiologie des Verhaltens. Göttingen, Gemany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D323-2
Zusammenfassung
Investigating face recognition with voices and face morphs Humans can easily identify faces at the individual level although faces belong to a class of objects with high similarity between exemplars. Characterizing conditions for which faces are more easily recognized allows us to better understand the mechanisms underlying face recognition. Numerous studies have shown that distinctive faces are better recognized than typical faces. Those results have implication for the mental representation of faces. In a set of experiments we tested cross-modal effects of distinctiveness. More specifically we asked whether distinctive voices can improve memory for otherwise typical faces. Our results suggest that the quality of information in one modality, i.e., audition, can affect recognition in another modality, i.e., vision; thus showing that face distinctiveness can be of multi-modal nature. Because we encounter faces of only two sexes but recognize faces of innumerable different identities, it is often implicitly assumed that sex classification is an easier task than identification. We investigated how sensitive we are to variations of identity-related features or sex-related features of highly familiar faces. The results suggest that while extracting and processing sex-related information from a face is a comparatively easy task, we do not seem to retain sex-related facial information in memory as accurately as identity-related information. These results have implications for models of face representation and face processing.