Open AccessConstruction of Sports Recognition System Based on Sports Visual Image Technology under the Background of Information Technology
Author(s) -
Shubing Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2066/1/012065
Subject(s) - athletes , squatting position , jumping , test (biology) , motion (physics) , artificial intelligence , raising (metalworking) , action (physics) , computer science , computer vision , multimedia , human–computer interaction , engineering , physical therapy , medicine , physiology , paleontology , mechanical engineering , physics , quantum mechanics , biology
With the development of the times, sports competitions are sought after and favored by more and more people, and the judgment of athletes in the competition is becoming more and more strict and standardized. The further development of Internet technology and information technology has provided great convenience for the effective recognition of athletes’ movements in sports competitions. This article aims to study the background of information technology, through the use of sports visual image technology to design and construct an action recognition system, in order to efficiently and accurately identify and judge the various movements of sports competitions, thereby effectively reducing various manpower and the cost of material resources, while improving the accuracy of the competition results. In the experiment, this article invites 100 volunteers to participate in the system’s behavioral test recognition. The volunteers’ simple exercises such as jumping, raising hands, kicking, turning and squatting are tested, and the result is the exercise designed in this article. The recognition system is able to recognize five sets of actions in the experiment, among which jumping is 97.66%, kicking is 98.13%, squatting is 97.62%, raising hand is 95.24%, and turning is 96.43%. Research shows that the motion recognition system based on sports visual image technology designed and constructed in this paper has high motion recognition accuracy and can recognize athletes’ movements scientifically and effectively.