View variations effect in gait recognition and performance improvement using fusion

This paper presents the view variations effect in gait recognition. Here different variation is created based on the walking in different angle of person with respect to particular line. Initially we are showing the result of what is the recognition rate when we are taking different view training and testing image. These results show that recognition through gait is affected by view variation. So we are using fusion strategy to improve the results. Here different view image are fuse using PCA algorithm. We are also showing the result of fusion based gait recognition in different view. All experiments are performed on CASIA gait data base. Our results show that fusion based gait recognition is more effective when we want recognition people in different view. Gait recognition is one kind of biometric technology that can be used to monitor people without their cooperation, it is also difficult to conceal.