Analysis of Gait Recognition Using SVM and Surf Algorithm a Review

Gait is a potential behavioral feature and many studies have demonstrated that it has a rich potential as a biometric for recognition. Vision based Posture Recognition has a potential to be a natural and power full tool supporting efficient institutive interface for HCI. In this paper a survey of recent Human Gait Recognition System is presented, its purpose is to introduce a visual interpretation of Gait Recognition as mechanism of interaction to identify the human in the application of Biometric Authentication. Simple feature selection Hanavan’s model reduce the computational cost significantly during training and recognition. These methods have been applied on frames of videos, and these videos are live and some from ADSC-AWD database. In visual observation frameworks, human ID at a separation has as of late picked up more investment. The advancement of workstation vision methods has additionally guaranteed that vision based programmed walk examination might be continuously attained for training and testing purpose.