Application of Human Movement and Movement Scoring Technology in Computer Vision Feature in Sports Training
Shuai Liu, Yangjun Liu · IETE Journal of Research · 2021
An important goal of computer vision research is to give computers human-like cognitive abilities so that the computer can recognize the environment in the visual field, understand the content of emotions, and take appropriate actions. Most of the information that people can perceive is obtained through vision. It is the human goal to make computers have the same visual functions as humans. At present, although computers do not have efficient, flexible, and intelligent human vision, with the joint efforts of researchers, people are gradually achieving their goals. The purpose of this thesis is to study the application of human movement and movement scoring technology in computer vision features in sports training. In this paper, the support vector machine (SVM) method is used to recognize the human movement in the video. After the recognition, the score is then performed, which can help sports athletes to carry out standardized training. The results of this paper show that the use of SVM method can basically achieve a recognition accuracy of more than 80% of human motion actions, so that motor actions can be scored better and more conveniently. Computer vision technology for action scoring can help athletes standardize various sports skills and improve their ability to compete by improving various sports skills.