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» On optimizing subspaces for face recognition
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ACCV
2007
Springer
14 years 1 months ago
Kernel Discriminant Analysis Based on Canonical Differences for Face Recognition in Image Sets
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...
TIP
2010
188views more  TIP 2010»
13 years 5 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
FGR
2006
IEEE
255views Biometrics» more  FGR 2006»
13 years 10 months ago
Incremental Kernel SVD for Face Recognition with Image Sets
Non-linear subspaces derived using kernel methods have been found to be superior compared to linear subspaces in modeling or classification tasks of several visual phenomena. Such...
Tat-Jun Chin, Konrad Schindler, David Suter
CVPR
2007
IEEE
14 years 9 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...
CVPR
2010
IEEE
13 years 10 months ago
Discriminative K-SVD for Dictionary Learning in Face Recognition
In a sparse-representation-based face recognition scheme, the desired dictionary should have good representational power (i.e., being able to span the subspace of all faces) while...
Qiang Zhang, Baoxin Li