PCA PLUS F-LDA: A NEW APPROACH TO FACE RECOGNITION
2007 ◽
Vol 21
(06)
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pp. 1059-1068
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Keyword(s):
A new feature extraction method for face recognition based on principal component analysis (PCA) and fractional-step linear discriminant analysis (F-LDA) is given in this paper. In order to reduce the computation complexity, PCA is first used to reduce the dimension. In addition, before using F-LDA, we transform the pooled within-class scatter matrix into an identity matrix. The proposed method is tested on AR and UMIST face databases. Experiment results show that our method gains higher classification accuracy than other existing methods used in the experiment.
2014 ◽
Vol 556-562
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pp. 4825-4829
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2014 ◽
Vol 568-570
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pp. 668-671
2019 ◽
Vol 33
◽
pp. 9963-9964
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2011 ◽
Vol 63-64
◽
pp. 55-58
2007 ◽
Vol 21
(08)
◽
pp. 1265-1278
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Keyword(s):
2015 ◽
Vol 29
(04)
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pp. 1556004
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