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...
—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...
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...
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...
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...