A SVM face recognition method based on Gabor-featured key points

This paper presents a novel face recognition approach based on support vector machine and Gabor-featured key points, which takes technological advantages of both support vector machine and Gabor feature extraction. The main contributions of this paper therefore lie in the following aspects: (1) support vector machine is successfully applied to face recognition by using Gabor features of key points; (2) Gabor features of key points are introduced to represent a whole face in a computable dimensional space. As a result, experiments on FERET and AT&T databases have shown significant better performance with this method, which in itself proves the feasibility of our proposal.