Title: Face recognition using kernel principal component analysis
Abstract:A kernel principal component analysis (PCA) was recently proposed as a nonlinear extension of a PCA.The basic idea is to first map the input space into a feature space via nonlinear mapping and then c...A kernel principal component analysis (PCA) was recently proposed as a nonlinear extension of a PCA.The basic idea is to first map the input space into a feature space via nonlinear mapping and then compute the principal components in that feature space.This letter adopts the kernel PCA as a mechanism for extracting facial features.Through adopting a polynomial kernel, the principal components can be computed within the space spanned by high-order correlations of input pixels making up a facial image, thereby producing a good performance.Read More