Automatic face authentication with self compensation
This paper presents a novel method for automatic face authentication in which the variance of faces due to aging has been considered. A bilateral symmetrical plane is used for weighting the correspondences of the scanned model and database model upon model verification. This bilateral symmetrical plane is determined by the nose tip and two canthus features. The coupled 2D and 3D feature extraction method is introduced to determine the positions of these canthus features. The central profile on this bilateral symmetrical plane is the foundation of the face recognition. A weighting function is used to determine the rational points for the correspondences of the optimized iterative closest point method. The discrepancy value is evaluated for the authentication and compensation between different models. We have implemented this method on the practical authentication of human faces. The result illustrates that this method works well in both self authentication and mutual authentication.
face authentication self compensation face recognition automatic feature detection