Dynamic gesture recognition based on improved DTW algorithm

Abstract

This paper aims at a dynamic gesture recognition method based on the improved DTW algorithm. Firstly, the 3D position of human skeletal points is obtained through the analysis of the depth information, which is obtained by SDK of the Kinect sensor. 8 points are selected as the hand movement characteristics, and the mathematical model of the gesture is established by the method of weighted distance. Then the DTW algorithm is improved by distortion threshold and the path constraints, which is used for training templates and dynamic gesture recognition. The results show that this method can realize the dynamic gesture recognition and have a good real-time performance and robustness. At the same time, the improved DTW algorithm has great improvement in speed and accuracy.