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  Role of featural and configural information in familiar and unfamiliar face recognition

Schwaninger, A., Lobmaier, J., & Collishaw, S. (2002). Role of featural and configural information in familiar and unfamiliar face recognition. In H. Bülthoff, C. Wallraven, S.-W. Lee, & T. Poggio (Eds.), Biologically Motivated Computer Vision: Second International Workshop, BMCV 2002 Tübingen, Germany, November 22–24, 2002 (pp. 243-250). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-DE5A-E Version Permalink: https://hdl.handle.net/21.11116/0000-0005-89A4-7
Genre: Conference Paper

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http://link.springer.com/content/pdf/10.1007%2F3-540-36181-2_64.pdf (Publisher version)
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 Creators:
Schwaninger, A1, 2, Author           
Lobmaier, JS, Author
Collishaw, SM, 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: Using psychophysics we investigated to what extent human face recognition relies on local information in parts (featural information) and on their spatial relations (configural information). This is particularly relevant for biologically motivated computer vision since recent approaches have started considering such featural information. In Experiment 1 we showed that previously learnt faces could be recognized by human subjects when they were scrambled into constituent parts. This result clearly indicates a role of featural information. Then we determined the blur level that made the scrambled part versions impossible to recognize. This blur level was applied to whole faces in order to create configural versions that by definition do not contain featural information. We showed that configural versions of previously learnt faces could be recognized reliably. In Experiment 2 we replicated these results for familiar face recognition. Both Experiments provide evidence in favor of the view that recognition of familiar and unfamiliar faces relies on featural and configural information. Furthermore, the balance between the two does not differ for familiar and unfamiliar faces. We propose an integrative model of familiar and unfamiliar face recognition and discuss implications for biologically motivated computer vision algorithms for face recognition.

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 Dates: 2002-11
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/3-540-36181-2_64
BibTex Citekey: 2029
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Title: Second International Workshop on Biologically Motivated Computer Vision (BMCV 2002)
Place of Event: Tübingen, Germany
Start-/End Date: 2002-11-22 - 2002-11-24

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Title: Biologically Motivated Computer Vision: Second International Workshop, BMCV 2002 Tübingen, Germany, November 22–24, 2002
Source Genre: Proceedings
 Creator(s):
Bülthoff, HH1, Editor           
Wallraven, C1, Editor           
Lee, S-W, Editor
Poggio, TA, Editor           
Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794            
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 243 - 250 Identifier: ISBN: 3-540-00174-3

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 2525 Sequence Number: - Start / End Page: - Identifier: -