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» Dual-Space Linear Discriminant Analysis for Face Recognition
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SCIA
2007
Springer
122views Image Analysis» more  SCIA 2007»
14 years 2 months ago
Individual Discriminative Face Recognition Models Based on Subsets of Features
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...
ICPR
2002
IEEE
14 years 9 months ago
Solving the Small Sample Size Problem of LDA
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scatter matrix Sw in Linear Discriminant Analysis (LDA...
Rui Huang, Qingshan Liu, Hanqing Lu, Songde Ma
TIP
2010
188views more  TIP 2010»
13 years 7 months ago
On-line Learning of Mutually Orthogonal Subspaces for Face Recognition by Image Sets
—We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by su...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
CVPR
2008
IEEE
13 years 10 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
ICPR
2008
IEEE
14 years 3 months ago
Linear discriminant analysis for data with subcluster structure
Linear discriminant analysis (LDA) is a widely-used feature extraction method in classification. However, the original LDA has limitations due to the assumption of a unimodal str...
Haesun Park, Jaegul Choo, Barry L. Drake, Jinwoo K...