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Optical Engineering • Open Access

Integrating affinity propagation clustering method with linear discriminant analysis for face recognition
Author(s): Chunhua Du; Jie Yang; Qiang Wu; Feng Li

Paper Abstract

The Fisherface method suffers from the problem of using all training face images to recognize a test face image. To tackle this problem, we propose combining a novel clustering method, affinity propagation (AP), recently reported in the journal Science, with linear discriminant analysis (LDA) to form a new method, AP-LDA, for face recognition. By using AP, a representative face image for each subject can be obtained. Our AP-LDA method uses only these representative face images rather than all training images for recognition. Thus, it is more computationally efficient than Fisherface. Experimental results on several benchmark face databases also show that AP-LDA outperforms Fisherface in terms of recognition rate.

Paper Details

Date Published: 1 November 2007
PDF: 3 pages
Opt. Eng. 46(11) 110501 doi: 10.1117/1.2801735
Published in: Optical Engineering Volume 46, Issue 11
Show Author Affiliations
Chunhua Du, Shanghai Jiao Tong Univ. (China)
Jie Yang, Shanghai Jiao Tong Univ. (China)
Qiang Wu, Univ. of Technology/Sydney (Australia)
Feng Li, Univ. of Delaware (United States)

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