Research on Badminton Teaching Technology Based on Human Pose Estimation Algorithm

Abstract

Human pose estimation is an important task in physical education, which can provide a valuable reference for teachers and students. We propose a human pose estimation method based on part affinity field. Firstly, the correlation of position information and orientation information between limb regions is maintained by part affinity field. Then the key points of limb pose are localized by part confidence map, and finally, the part affinity field is integrated to correlate all the acquired feature key points to obtain the human pose estimation. With the aid of computer vision technology, the students’ training movements can be compared with the standard movements. It enables the students to feel the standard movements and badminton hitting points more intuitively. In the experiment, we set up a comparison experiment to compare the teaching mode of the method in this paper with the traditional teaching mode. The experimental results prove that through the teaching mode of our method, students have more standard strokes, more smooth skill switching between badminton serves and strokes, and higher badminton stroke scores. At the same time, such a teaching system adds a lot of fun to the course and makes the students’ participation higher.