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.