Polynomial features for robust face authentication

Abstract

We introduce the DCT-mod2 facial feature extraction technique which utilizes polynomial coefficients derived from 2D DCT coefficients of spatially neighbouring blocks. We evaluate its robustness and performance against three popular feature sets for use in an identity verification system subject to illumination changes. Results on the multi-session VidTIMIT database suggest that the proposed feature set is the most robust, followed by (in order of robustness and performance): 2D Gabor wavelets; 2D DCT coefficients; PCA (eigenface) derived features. Moreover, compared to Gabor wavelets, the DCT-mod2 feature set is over 80 times quicker to compute.