EXPRESSION-INDEPENDENT FACE RECOGNITION USING BIOLOGICALLY INSPIRED FEATURES
Reza Ebrahimpour, Ahmad Jahani, Ali Amiri, Masoom Nazari · 2011
This paper presents an effective two-dimensional Expression-Independent face recognition method, based on features inspired by the human’s visual ventral stream. A feature set is extracted by means of a feed-forward model, which contains illumination and view invariant C2 features from all images in the dataset. Then, these C2 feature vectors which derived from a cortex-like mechanism passed to a standard Nearest Neighbor classifier. We evaluated the proposed approach on JAFEE database. The results show that this model is an efficient and high accurate face recognition algorithm that is robust to facial expressions. Experiments indicate that the proposed approach maintains high recognition rate and outperforms the other alternative methods such as PCA and 2DPCA. The improvement in performance than PCA and 2DPCA based methods is about 5% and 4.5% respectively.