Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
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...
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Robustness and discriminability are two key issues in face recognition. In this paper, we propose a new algorithm which extracts micro-structural Gabor feature to achieve good robu...
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...