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» Boosting linear discriminant analysis for face recognition
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CVPR
2005
IEEE
14 years 7 months ago
A Framework of 2D Fisher Discriminant Analysis: Application to Face Recognition with Small Number of Training Samples
A novel framework called 2D Fisher Discriminant Analysis (2D-FDA) is proposed to deal with the Small Sample Size (SSS) problem in conventional One-Dimensional Linear Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
TIP
2010
188views more  TIP 2010»
13 years 6 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
PRL
2010
188views more  PRL 2010»
13 years 6 months ago
Sparsity preserving discriminant analysis for single training image face recognition
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Lishan Qiao, Songcan Chen, Xiaoyang Tan
ICIP
2002
IEEE
14 years 9 months ago
A kernel machine based approach for multi-view face recognition
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
Juwei Lu, Kostas N. Plataniotis, Anastasios N. Ven...
ICMCS
2007
IEEE
159views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Boosting Face Retrieval by using Relevant Set Correlation Clustering
We present a method to improve the performance of face retrieval in news videos by using the relevant-set correlation (RSC) clustering model. In this method, faces of a person are...
Duy-Dinh Le, Shin'ichi Satoh, Michael E. Houle