A new approach to appearance-based face recognition
Current holistic appearance based face recognition methods require a high dimensional feature space to attain fruitful performance. In this paper, we have proposed a relatively low feature dimensional, template-matching scheme to cope with the transformed appearance-based face recognition problem. We use aggregated Gabor filter responses to represent face images. We investigated the effect of "duplicate" images (images from different sessions) and the effect of facial expressions. Our results indicate that the proposed method is more robust in recognizing "duplicate" images with variations in facial expression than the principal component analysis method.