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An eigenfaces-based automatic face recognition system

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3 Author(s)
E. Lizama ; Fraunhofer Inst. for Production Syst. & Design Technol., Berlin, Germany ; D. Waldoestl ; B. Nickolay

The problem of automatic face recognition (AFR) alone is a difficult task that involves detection and location of faces in a cluttered background, facial feature extraction, subject identification and verification. The main challenge lies in facial feature extraction. This should reduce the intra-person variability (due to changes in geometry, illumination, gesture, and biological changes) and increase the inter-person variability. Various approaches have previously been proposed, including the eigenfaces for which satisfactory experimental results have been reported. The eigenfaces approach assumes that the data is intrinsically low-dimensional. This contribution presents an eigenfaces-based AFR, that guarantees the low-dimensionality assumption by preprocessing steps and multiple eigenspaces. The necessity for pre-processing steps has already been recognized by other groups. In this paper, the need for multiple eigenspaces and the corresponding operative criterion is established

Published in:

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on  (Volume:1 )

Date of Conference:

12-15 Oct 1997