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» Boosting linear discriminant analysis for face recognition
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NIPS
2004
13 years 9 months ago
Efficient Kernel Discriminant Analysis via QR Decomposition
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
PR
2007
127views more  PR 2007»
13 years 7 months ago
Face recognition using spectral features
Face recognition is a challenging task in computer vision and pattern recognition. It is well-known that obtaining a low-dimensional feature representation with enhanced discrimin...
Fei Wang, Jingdong Wang, Changshui Zhang, James T....
CVPR
2010
IEEE
13 years 6 months ago
Cost-Sensitive Subspace Learning for Face Recognition
Conventional subspace learning-based face recognition aims to attain low recognition errors and assumes same loss from all misclassifications. In many real-world face recognition...
Jiwen Lu, Tan Yap-Peng
PAMI
2007
249views more  PAMI 2007»
13 years 7 months ago
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
— The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem...
Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Ma...
JCIT
2008
117views more  JCIT 2008»
13 years 7 months ago
The New Face Recognition Technique With the use of PCA and LDA
Image recognition using various image classifiers is an active research area. In this paper we will describe a new face recognition method based on PCA (Principal Component Analys...
Seyed Zeinolabedin Moussavi, Saeedreza Ehteram, Al...