Kernel Nearest Features Classifier for Face Recognition
Cairong Zou · 2006
Kernel-based nearest feature classifiers are proposed in this paper,which can directly classify original face images and need not extract features beforehand. Besides,two KNFS methods are proposed,one is generalization of KNFP and the other employs KPCA to construct nonlinear feature subspace.Experimental results on ORL and YALE database demonstrate the feasibility of the proposed methods.