Learning of Martial Arts Action Decomposition Method Based on Image Recognition

Abstract

In order to improve the effective guidance of martial arts movements, a decomposition method of martial arts movements based on image recognition is proposed. First of all, visual image target sampling of martial arts action is performed, and most of the noise background is eliminated through morphological gradient operation. Then, the contour edge of the human body is obtained, the contour edge of each frame of the video is extracted, and the accumulation is realized in the same image. Using accumulation, the edge image calculates the grid-based HOG to obtain the image action feature vector. Secondly, using the improved dynamic time warping theory combined with the characteristics of the angle change of each joint under the action time sequence, the joint change sequence among various martial arts movements can be identified in order to realize the decomposition process of martial arts actions based on image recognition. The experimental results show that the use of image recognition can effectively decompose martial arts movements.