An analytical algorithm for determining the generalized optimal set of discriminant vectors
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摘要
Generalized linear discriminant analysis has been successfully used as a dimensionality reduction technique in many classification tasks. An analytical method for finding the optimal set of generalized discriminant vectors is proposed in this paper. Compared with other methods, the proposed method has the advantage of requiring less computational time and achieving higher recognition rates. The results of experiments conducted on the Olivetti Research Lab facial database show the effectiveness of the proposed method.
论文关键词:Feature extraction,Generalized optimal discriminant vectors,Face recognition,LDA
论文评审过程:Received 11 July 2003, Accepted 25 July 2003, Available online 20 May 2004.
论文官网地址:https://doi.org/10.1016/j.patcog.2003.07.014