A rule-based approach for improving Kinect Skeletal Tracking system with an application on standard Muay Thai maneuvers

The release of Xbox 360 Kinect has made a triumph impression of computer vision technology and open a new world of gaming experience. Behind this leading success is an intelligent recognition system. The fundamental process is the transformation of depth images into skeleton data. Though this system is not without its flaws. Kinect Skeletal Tracking system fails when it comes to rapidly moving sequences of postures, when parts of body are out of the line of sight of the camera or when the postures are not in natural human forms. Such movements can be found in standard Muay Thai maneuvers. In this paper, we propose an algorithm to improve the rate of skeleton recognition in such scenarios. With the Kinect recognition system alone, the accuracy of skeleton recognitions of all 24 standard Muay Thai maneuvers is 51%. After applying our proposed algorithm, we are able to bring the accuracy up 26%. On average, our proposed algorithm along with the Kinect recognition system yields accuracy of 77% on average standard Muay Thai maneuvers.