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CIVR
2007
Springer
169views Image Analysis» more  CIVR 2007»
9 years 4 months ago
Whitened LDA for face recognition
Over the years, many Linear Discriminant Analysis (LDA) algorithms have been proposed for the study of high dimensional data in a large variety of problems. An intrinsic limitatio...
Vo Dinh Minh Nhat, Sungyoung Lee, Hee Yong Youn
ICPR
2006
IEEE
9 years 4 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 2 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
FGR
2008
IEEE
214views Biometrics» more  FGR 2008»
9 years 4 months ago
Normalized LDA for semi-supervised learning
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Bin Fan, Zhen Lei, Stan Z. Li
ICB
2009
Springer
140views Biometrics» more  ICB 2009»
9 years 5 months ago
A Discriminant Analysis Method for Face Recognition in Heteroscedastic Distributions
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of diļ¬€erent classes are obey to t...
Zhen Lei, ShengCai Liao, Dong Yi, Rui Qin, Stan Z....
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