Gait Recognition for Saudi Costume Using Kinect Skeletal Tracking

Abstract

Gait is a cutting-edge biometric for recognizing people. Gait data can be captured reliably even from long distances, and it is difficult to cover up or copy. In this paper, we have explored the use of Kinect for gait identification of Saudi persons who are wearing thobe or abaya. These garments hide most of the joints and so gait recognition becomes a challenge. Our algorithm uses Kinect to identify the top three joints that could give the best identification results and then uses them for gait recognition. Features used are the Y coordinates of joints and classifier used is K Nearest Neighbor.