English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Meeting Abstract

Component and configural information in view‐based face recognition

MPS-Authors
/persons/resource/persons84420

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;

/persons/resource/persons84298

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;

/persons/resource/persons83839

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

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Schwaninger, A., Schumacher, S., Wallraven, C., & Bülthoff, H. (2004). Component and configural information in view‐based face recognition. International Journal of Psychology, 39(5-6): 3073.3, 283.


Cite as: https://hdl.handle.net/21.11116/0000-0003-62E0-1
Abstract
Everyday life requires us to identify different faces in many different poses and views. In this study we used the inter‐extra‐ortho paradigm from Bülthoff & Edelman (1992) in order to investigate what kinds of information are used for recognizing faces across viewpoint. The results of three experiments provided clear evidence that faces are encoded, stored and recognized across viewpoint using component and configural information. Moreover, it was found that part‐based processing is substantially more viewpoint dependent than processing configural information. Systematic effects of viewpoint are discussed in a computational framework based on key frames that allowed modelling the psychophysical data.