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TCSV
2008
195views more  TCSV 2008»
13 years 6 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
13 years 10 months ago
Spectral Regression: A Unified Approach for Sparse Subspace Learning
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Deng Cai, Xiaofei He, Jiawei Han
CIVR
2008
Springer
271views Image Analysis» more  CIVR 2008»
13 years 8 months ago
Multiple feature fusion by subspace learning
Since the emergence of extensive multimedia data, feature fusion has been more and more important for image and video retrieval, indexing and annotation. Existing feature fusion t...
Yun Fu, Liangliang Cao, Guodong Guo, Thomas S. Hua...
CVPR
2009
IEEE
15 years 1 months ago
Coupled Spectral Regression for Matching Heterogeneous Faces
Face recognition algorithms need to deal with variable lighting conditions. Near infrared (NIR) image based face recognition technology has been proposed to effectively overcome...
Stan Z. Li, Zhen Lei
FGR
2008
IEEE
214views Biometrics» more  FGR 2008»
14 years 21 days 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