Research on Two Dimensional Nonparametric Discriminant Analysis for Face Recognition

A novel method for face recognition based on two dimensional nonparametric discriminant analysis is proposed. Traditional LDA-based methods suffer in disadvantages such as small sample size problem (SSS), a dimensionality, as well as a fundamental limitation resulting from the parametric nature of scatter matrices, which are based on the Gaussian distribution assumption. To address the problem, a new two dimensional nonparametric discriminant analysis is proposed, a new formulation of scatter matrices is given. Experimental results indicate the robustness and accuracy of the proposed method.