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Dynamic Faces: Insights from Experiments and Computation

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83871

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83839

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84787

Giese,  MA
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Curio, C., Bülthoff, H., & Giese, M. (2010). Dynamic Faces: Insights from Experiments and Computation.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-BDA8-2
Zusammenfassung
The recognition of faces is a fundamental visual function with importance for social interaction and communication. Scientific interest in facial recognition has increased dramatically over the last decade. Researchers in such fields as psychology, neurophysiology, and functional imaging have published more than 10,000 studies on face processing. Almost all of these studies focus on the processing of static pictures of faces, however, with little attention paid to the recognition of dynamic faces, faces as they change over time—a topic in neuroscience that is also relevant for a variety of technical applications, including robotics, animation, and human-computer interfaces. This volume offers a state-of-the-art, interdisciplinary overview of recent work on dynamic faces from both biological and computational perspectives. The chapters cover a broad range of topics, including the psychophysics of dynamic face perception, results from electrophysiology and imaging, clinical deficits in patients with impairments of dynamic face processing, and computational models that provide insights about the brain mechanisms for the processing of dynamic faces. The book offers neuroscientists and biologists an essential reference for designing new experiments, and provides computer scientists with knowledge that will help them improve technical systems for the recognition, processing, synthesizing, and animating of dynamic faces.