de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Talk

Computational modeling of face recognition

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84298

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84420

Schwaninger,  A
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;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Wallraven, C., Schwaninger, A., & Bülthoff, H. (2003). Computational modeling of face recognition. Talk presented at 44th Annual Meeting of The Psychonomic Society. Vancouver, Canada.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-DB0F-E
Abstract
Recent psychophysical results on face recognition (Schwaninger et al., 2002) support the notion that processing of faces relies on two separate routes. The first route processes highdetail components of the face (such as eyes, mouth, etc.), whereas the second route processes the configural relationship between these components. This model was successfully used to explain several aspects of face recognition, such as the Thatcher Illusion or the stimuli composed by Young et al. (1987). We discuss a computational framework, in which we implemented configural and component processing using image fragments and their spatial layout. Using the stimuli from the original psychophysical study, we were able to model the recognition performance. In addition, large-scale tests with highly realistic computer-rendered faces from the MPI database show better performance and robustness than do other computational approaches using one processing route only.