Research on monitoring volleyball players’ competition load based on intelligent tracking technology

Abstract To evaluate volleyball players' sports activities using the author's own video recording system. They tested 28 volleyball players in four games for the Polish Volleyball League Plus and the Federation of Europe. Record data were analyzed for groups in matches given the average total distance covered by the volleyball players in different meetings' specialties. The research programs that extend the finals' players' distance set indicate these individual meetings' long-term trend. It is crucial to monitor the training load to essential the state together to prevent unnecessary changes. Knowledge of these variables during the volleyball season is still lacking—objective: To describe competitive volleyball players' training load and recovery status during the monitoring season. The purpose of this research is to describe and explore professional volleyball players throughout the season for Internal Training Load (ITL), recovery and body distribution. Recipe: 15 professional male Brazilian volleyball players participated. The target's three-dimensional position monitoring technology is beneficial for analysis and professional understanding of volleyball games. Still, many factors make any change in the rate of sports volleyball tracking. This article describes the image processing technology combined with 3D space matching technology. It features a particle filter, effectively enhancing volleyball tracking accuracy, tracking a game system's structure. Second, the proposed similarity prediction method is based on the properties of volleyball itself, mainly to solve supercomputing in real-time monitoring based on the similarity prediction of alkali and HSV color spaces. Finally, the simulation test results show that this method can significantly improve the tracking success rate—high efficiency and high accuracy dynamic video game tracking properties unexpected value development value volleyball.