Weighting Estimation for Texture-Based Face Recognition Using the Fisher Discriminant

Texture-based automatic face recognition (AFR) methods find global similarities between two faces by computing their local regional similarities. A novel method based on Fisher discriminant analysis is proposed to estimate each region's contribution to the global similarity score. Experimental results show that the method considerably improves recognition performance for texture-based AFR.