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Subspace Linear Discriminant Analysis for Face Recognition

Wenyi Zhao

出版	Computer Vision Laboratory, Center for Automation Research, University of Maryland, 1999
URL	http://books.google.com.hk/books?id=yVvxGwAACAAJ&hl=&source=gbs_api

註釋

In this paper we describe a holistic face recognition method based on subspace Linear Discriminant Analysis (LDA). The method consists of two steps: first we project the face image from the original vector space to a face subspace via Principal Component Analysis where the subspace dimension is carefully chosen, and then we use LDA to obtain a linear classifier in the subspace. The criterion we use to choose the subspace dimension enables us to generate class-separable