Motion Features from Lip Movement for Person Authentication

This paper describes a new motion based feature extraction technique for speaker identification using orientation estimation in 2D manifolds. The motion is estimated by computing the components of the structure tensor from which normal flows are extracted. By projecting the 3D spatiotemporal data to 2D planes, we obtain projection coefficients which we use to evaluate the 3D orientations of brightness patterns in TV like image sequences. This corresponds to the solutions of simple matrix eigenvalue problems in 2D, affording increased computational efficiency. An implementation based on joint lip movements and speech is presented along with experiments which confirm the theory, exhibiting a recognition rate of 98% on the publicly available XM2VTS database©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.