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Processing of facial identity and expression: a psychophysical, physiological, and computational perspective

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Schwaninger,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Wallraven,  C
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Cunningham,  DW
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Schwaninger, A., Wallraven, C., Cunningham, D., & Chiller-Glaus, S. (2006). Processing of facial identity and expression: a psychophysical, physiological, and computational perspective. In S. Anders, G. Ende, M. Junghofer, J. Kissler, & D. Wildgruber (Eds.), Understanding Emotions (pp. 321-343). Amsterdam, The Netherlands: Elsevier.


Cite as: http://hdl.handle.net/21.11116/0000-0004-9D4F-4
Abstract
A deeper understanding of how the brain processes visual information can be obtained by comparing results from complementary fields such as psychophysics, physiology, and computer science. In this chapter, empirical findings are reviewed with regard to the proposed mechanisms and representations for processing identity and emotion in faces. Results from psychophysics clearly show that faces are processed by analyzing component information (eyes, nose, mouth, etc.) and their spatial relationship (configural information). Results from neuroscience indicate separate neural systems for recognition of identity and facial expression. Computer science offers a deeper understanding of the required algorithms and representations, and provides computational modeling of psychological and physiological accounts. An interdisciplinary approach taking these different perspectives into account provides a promising basis for better understanding and modeling of how the human brain processes visual information for recognition of identity and emotion in faces.