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A search advantage for faces learned in motion

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84141

Pilz,  KS
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84258

Thornton,  IM
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;

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Zitation

Pilz, K., Thornton, I., & Bülthoff, H. (2006). A search advantage for faces learned in motion. Experimental Brain Research, 171(4), 436-447. doi:10.1007/s00221-005-0283-8.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D115-1
Zusammenfassung
Recently there has been growing interest in the role that motion might play in the perception and representation of facial identity. Most studies have considered old/new recognition as a task. However, especially for non-rigid motion, these studies have often produced contradictory results. Here, we used a delayed visual search paradigm to explore how learning is affected by non-rigid facial motion. In the current studies we trained observers on two frontal view faces, one moving non-rigidly, the other a static picture. After a delay, observers were asked to identify the targets in static search arrays containing 2, 4 or 6 faces. On a given trial target and distractor faces could be shown in one of five viewpoints, frontal, 22 or 45 degrees to the left or right. We found that familiarizing observers with dynamic faces led to a constant reaction time advantage across all set sizes and viewpoints compared to static familiarization. This suggests that non-rigid motion affects identity decisions even across exten ded periods of time and changes in viewpoint. Furthermore, it seems as if such effects may be difficult to observe using more traditional old/new recognition tasks.