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  Face Recognition across Large Viewpoint Changes

O'Toole, A., Bülthoff, H., Troje, N., & Vetter, T.(1995). Face Recognition across Large Viewpoint Changes (9).

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 Creators:
O'Toole, AJ1, Author           
Bülthoff, HH1, Author           
Troje, NF1, Author           
Vetter, T1, Author           
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Abstract: We describe a computational model of face recognition that makes use of the overlapping texture and shape information visible in different views of faces. The model operates on view dependent data from three-dimensional laser scans of human heads, which provided three-dimensional surface data as well as surface image detail in the form of a texture map. View-dependent information from these surface and texture representations was registered onto separate three-dimensional head models. We used an auto-associative memory model as a pattern completion device to fill in parts of the head from a learned view when a test view with partially overlapping information was used as a memory key. We show that the overlapping visible regions of heads for both surface and texture data can support accurate recognition, even with pose differences of as much as 90 degrees (full face to profile view) between the learning and test view.

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 Dates: 1995-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Report Nr.: 9
BibTex Citekey: 1468
 Degree: -

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