Paper Title
Multimodal Human Identification System Based Fusion Using Gait Biometrics

Abstract— In this paper describe a method for multi-view multi-modal biometrics from a single walking image sequence. As multi modal cues, we adopt not only face and gait but also the actual height of a person, all of which are simultaneously captured by a single camera. As multi-view cues, we use the variation in the observation views included in a single image sequence captured by a camera with a relatively wide field of view. This enables us to improve the authentication of a person based on multiple modalities and views, Gait image Is represented by the Active Horizontal level (AHL) feature vector. The proposed system was tested on CASIA database and the achieved results showed that the integrated gait features carry the most discriminating power compared to any individual biometric.