A real-time dynamic hand gesture recognition system using kinect sensor

The use of hand gestures provides an attractive alternative to cumbersome interface devices for Human-Computer Interaction (HCI). However, in dynamic gesture recognition area, hand tracking under a complicated environment and gesture spotting namely detecting the start and end point are the two most challenging topics. In our work, a realtime Kinect-based dynamic hand gesture recognition (HGR) system which contains hand tracking, data processing, model training and gesture classification is proposed. In the first stage, two states of the performed hand including open and closed are utilized to achieve gesture spotting and 3D motion trajectories of gestures are captured by Kinect sensor. Further, motion orientation is extracted as the unique feature and Support Vector Machine (SVM) is used as the recognition algorithm in the proposed system. The results of experiments conducted in our database containing 10 Arabic numbers from 0 to 9 and the 26 characters of alphabet show efficiency with an average recognition rate of 95.42% and real-time performance of our method.