Research on face recognition method based on PCA

Abstract

Principal component analysis (PCA) is one of the most widely used face feature extraction methods, and has evolved a lot of new algorithms, which has become a hot research topic. It [1] is a multivariate statistical method, can effectively reduce the dimension of the face image, and can keep the original data of most of the major information, has been widely used in the field of pattern recognition and computer vision. This paper introduces the basic principles of PCA, as well as the improved PCA algorithm, and finally the simulation experiments are carried out.