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  Learning from humans: computational modeling of face recognition

Wallraven, C., Schwaninger, A., & Bülthoff, H. (2004). Learning from humans: computational modeling of face recognition. In Early Cognitive Vision Workshop (ECOVISION 2004) (pp. 1-4).

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D8EB-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-5366-B
Genre: Conference Paper

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 Creators:
Wallraven, C1, 2, Author              
Schwaninger, A1, 2, Author              
Bülthoff, HH1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: In this paper we propose a computational architecture of face recognition based on evidence from cognitive research. Using an implementation of this architecture we were able to model aspects of human performance, which were found in psychophysical studies. Furthermore, results from additional recognition experi ments show that our framework is able to achieve excellent recognition performance even under large view rotations. Thus, our study is an example of how results from cognitive research can be used to construct recognition systems with better performance. Finally, our results also make new experimental predictions, which can be tested in further psychophysical studies thus closing the loop between experiment and modeling.

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 Dates: 2004-05
 Publication Status: Published online
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 Identifiers: BibTex Citekey: 2272
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Title: Early Cognitive Vision Workshop (ECOVISION 2004)
Place of Event: Skye, Scotland, UK
Start-/End Date: 2004-05-29

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Title: Early Cognitive Vision Workshop (ECOVISION 2004)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 4 Identifier: -