@conference {12692,
	title = {Multiple-exemplar discriminant analysis for face recognition},
	booktitle = {Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
	volume = {4},
	year = {2004},
	month = {2004/08//},
	pages = {191 - 194 Vol.4 - 191 - 194 Vol.4},
	abstract = {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. 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.},
	keywords = {analysis;, database;, databases;, discriminant, Face, FERET, multiple-exemplar, recognition;, visual},
	doi = {10.1109/ICPR.2004.1333736},
	author = {Zhou,S. K and Chellapa, Rama}
}
