Robust Face Recognition Method Based on Kernel Regularized Relevance Weighted Discriminant Analysis and Deterministic Approach

A novel feature dimensionality reduction strategy based on kernel regularized relevance weighted discriminant analysis is proposed in this paper with some interesting characteristics. First, the proposed method has shown its effectiveness in dealing with a small sample size problem when using the regularized linear discriminant analysis (RLDA) technique and Kernel theory. Second, a new computation method is proposed to solve the complicated and inefficient computation procedure problem in the traditional RLDA technique while using the cross-validation method. The experimental results indicate that the proposed algorithm shows better performance than the other methods.