Application of optical image processing technology based on priority scheduling algorithm in mobile terminal sports training assistance system

Abstract

Abstract Due to the difficulty of basic volleyball techniques, many students find it difficult to master correct motor skills in a short period of time. By utilizing virtual coaches provided by artificial intelligence technology, students can receive more comprehensive and systematic volleyball technical training. This article introduces a volleyball decision-making assistance system based on artificial intelligence and system task scheduling algorithms. The system uses computer vision and machine learning technologies such as image recognition, object tracking, Motion planning, etc., to realize real-time tracking and analysis of players and balls in volleyball matches, and assist players in making tactics and decisions. The system first collects images on the field through a camera, and achieves real-time tracking of athletes and balls through image processing technology. Then, machine learning algorithms are used to predict and analyze the trajectory of athletes and balls, as well as to judge and predict the situation on the field. Finally, through task scheduling algorithms, the optimal tactics and decisions are formulated to provide real-time sports decision-making and assistance for athletes. The experimental results indicate that the system can effectively assist athletes in decision-making and tactical formulation in volleyball matches, improving the winning rate and competitiveness of the competition.