Fusion of LDA and PCA for Face Recognition

Although many approaches for face recognition have been proposed in the last years, none of them can overcome the main problem of this kind of biometrics: the huge variability of many environmental parameters (lighting, pose, scale). Hence, face recognition systems can achieve good results at the expense of robustness. In this work we describe a methodology for improving the robustness of a face recognition system based on the “fusion” of two well-known statistical representations of a face: PCA and LDA. Experimental results that confirm the benefits of fusing PCA and LDA are reported.