Gait Recognition from Front and Back View Sequences Captured Using Kinect

Abstract

In this paper, we propose a key pose based gait recognition approach using skeleton joint information derived from the depth data of Kinect. We consider situations where such depth cameras are mounted on top of entry and exit points, respectively capturing back and front views of subjects who enter a zone under surveillance. Three dimensional geometric transformations are used to map the skeleton images captured from the back view to an equivalent front view. A gait cycle is divided into a number of key poses and the trajectory followed by each skeleton joint within a key pose is used to derive the gait features for that particular pose. For recognizing a subject, available key poses are compared with the corresponding key poses of the training subjects. The proposed method has higher accuracy than other competing approaches.