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AMFG
2005
IEEE
152views Biometrics» more  AMFG 2005»
9 years 9 months ago
Regularization of LDA for Face Recognition: A Post-processing Approach
When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null s...
Wangmeng Zuo, Kuanquan Wang, David Zhang, Jian Yan...
ICPR
2004
IEEE
10 years 5 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 analysi...
Rama Chellappa, Shaohua Kevin Zhou
ICIP
2004
IEEE
10 years 5 months ago
Regularization studies on LDA for face recognition
It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
ICPR
2006
IEEE
9 years 10 months ago
Face Recognition Using Angular LDA and SVM Ensembles
One successful approach to feature extraction in face recognition problems is that of linear discriminant analysis (LDA). We examine an extension of this technique, called angular...
Raymond S. Smith, Josef Kittler, Miroslav Hamouz, ...
FGR
2004
IEEE
200views Biometrics» more  FGR 2004»
9 years 7 months ago
Using Random Subspace to Combine Multiple Features for Face Recognition
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
Xiaogang Wang, Xiaoou Tang
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