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Multiple-Exemplar Discriminant Analysis for Face Recognition

9 years 11 months ago
Multiple-Exemplar Discriminant Analysis for Face Recognition
Face recognition is characteristically different from regular pattern recognition and, therefore, requires a different discriminant analysis other than linear discriminant analysis (LDA). LDA is a single-exemplar method in the sense that each class during classification is represented by a single exemplar, i.e. the sample mean of the class. In this paper, we present a multiple-exemplar discriminant analysis (MEDA) where each class is represented using several exemplars or even the whole available sample set. The proposed approach produces improved classification results when tested on a subset of FERET database where LDA is ineffective.
Rama Chellappa, Shaohua Kevin Zhou
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Rama Chellappa, Shaohua Kevin Zhou
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