An optimal tradeoff synthetic discriminant function filter based still-to-video face verification system

Face image is an attractive biometric for person verification and identification because face images can be obtained non-intrusively, even without the knowledge of the subject in some cases. But in the case that the subject is non-cooperative (in the sense of providing a predefined view for testing), the still-to-still face verification method may have difficulty in matching face images from two different view angles. In this paper we propose a still-to-video face verification method based on the optimal tradeoff synthetic discriminant function (OTSDF) filter technology for the scenario where the video sequence of a subject is available for testing. The system consists of face detection and tracking component, frame level face matching component and the evidence accumulation component. We also investigate the part-based correlation method.