A novel face recognition algorithm based on PCA

The research in this paper is driven by the need to design a face recognition method, which would be able to cope with unconstrained variations in illumination, and head pose between images of the same individual. The main novelty of this work is the idea that some of the local facial features of the same individual do not vary even when the facial expression, illumination and pose vary. This idea is applied to the principal component analysis (PCA) method to arrive at a new method called composite PCA. The accuracy of the conventional PCA method and composite PCA method are evaluated under the conditions of varying expression, illumination and pose using standard databases. The composite PCA technique is found to be more accurate than the conventional PCA method under these conditions. Another advantage of the proposed method is the significant reduction in training time for the computation of principal components.