Artificial Intelligence-Based Joint Movement Estimation Method for Football Players in Sports Training

• Main Authors: Bin Zhang, Ming Lyu, Lei Zhang, Yang Wu
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Mobile Information Systems
• Online Access: http://dx.doi.org/10.1155/2021/9956482

Football is a product in the process of human socialization; it can strengthen the body and enhance the ability of teamwork. The introduction of artificial intelligence into football training is an inevitable trend; this trend must be bound to intensify, but how to apply artificial intelligence to solve the problem of the joint movement estimation method for football players in sports training is still the main difficulty now. The basic principle of football training action pattern recognition is to determine the type of football player’s action by processing and analyzing the movement information obtained by the sensor. Due to the complex movements towards football players and the changeable external environment, there are still many problems with action recognition. Focusing on the detailed classification of different sports modes, this article conducts research on the recognition of the joint movement estimation method for football players in sports training. This paper uses the recognition algorithm based on the multilayer decision tree recognizer to identify the joint movement; the experiment shows that the method used in this paper accurately identified joint movement for football players in sports training.