To improve the effect of traditional eigenface method on face recognition under large illumination variation, a new face recognition method was proposed. Unlike second -order PCA face recognition, it used independent component analysis on the PCA residual eigenfaces instead of principal component analysis to extract the independent component feature, and integrated the IC feature in PCA residual face space with the IC feature in original face space to be the ultimate feature for recognition. Experiments prove that it is more efficient than some conventional human face recognition methods, such as eigenface based method, ICA based method, and second-order PCA method, under large illumination and pose variations, and also has a good practicability.
