Multimodal gait recognition based on stereo vision and 3D template matching

Homeland security functions focus on intelligence and warning, protecting critical infrastructure and domestic counterterrorism. Biometric is a reliable way to authenticate the identity of a living person based on the physiological or behavioral characteristics. Vision based human identification at a distance has gained more attention. In this paper, a novel method for improving the authentication accuracy is proposed by combining stereovision technique with 3D template matching method. An HMM analysis is also performed in parallel to improve the accuracy of recognition. The two processes are computed separately and the values are compared against the existing database. The images computed are samples stored in the Carnegie Melon University database.