Improving the Recognition and Analysis of the Surendra Algorithm in Athletes’ Motion Capture

Abstract

With the development of computer technology, its application in athletes’ motion capture is more and more extensive, which can be used to design suitable sensors by the Surendra algorithm. In recent years, more and more scholars have begun to use motion capture technology to study human motion posture, analyze and study human motion posture data and apply it to people’s work, study and life. Motion capture technology has also become a key technology in the field of human motion posture research and is playing an increasingly important role. In this paper, a three-dimensional skeletal model of the athlete’s body is first established based on dynamics, and the athlete’s movement characteristics are simulated by this model. Then, the athlete’s movement posture is judged to determine the appropriate form of movement expression. Then, the improved Surendra algorithm is used to detect the movement movements.