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» Line-Based PCA and LDA Approaches for Face Recognition
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ICPR
2004
IEEE
14 years 9 months ago
Illumination and Expression Invariant Face Recognition with One Sample Image
Most face recognition approaches either assume constant lighting condition or standard facial expressions, thus cannot deal with both kinds of variations simultaneously. This prob...
Brian C. Lovell, Shaokang Chen
TSMC
2008
182views more  TSMC 2008»
13 years 8 months ago
Incremental Linear Discriminant Analysis for Face Recognition
Abstract--Dimensionality reduction methods have been successfully employed for face recognition. Among the various dimensionality reduction algorithms, linear (Fisher) discriminant...
Haitao Zhao, Pong Chi Yuen
AVBPA
2003
Springer
78views Biometrics» more  AVBPA 2003»
14 years 1 months ago
Resampling for Face Recognition
Abstract. A number of applications require robust human face recognition under varying environmental lighting conditions and different facial expressions, which considerably vary ...
Xiaoguang Lu, Anil K. Jain
CVPR
2007
IEEE
14 years 10 months ago
Learning a Spatially Smooth Subspace for Face Recognition
Subspace learning based face recognition methods have attracted considerable interests in recently years, including Principal Component Analysis (PCA), Linear Discriminant Analysi...
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han, Thoma...
ACCV
2006
Springer
14 years 2 months ago
Occlusion Invariant Face Recognition Using Selective LNMF Basis Images
In this paper, we propose a novel occlusion invariant face recognition algorithm based on Selective Local Nonnegative Matrix Factorization (S-LNMF) technique. The proposed algorith...
Hyun Jun Oh, Kyoung Mu Lee, Sang Uk Lee, Chung-Hyu...