Original article
DOI: 10.15293/1812-9463.2403.11
Boris A. Shriner
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Konstantin M. Zhomin
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Abstract. Introduction. The article presents the areas of use of computer vision technologies in the field of physical education and sports activities. Methodology. Innovative methods for assessing motor action based on video material, pattern recognition, object tracking are analyzed, the possibility of automated control of motor action based on the use of artificial intelligence and neural networks is shown. Particular attention is paid to the possibilities to integrate computer vision technologies from the field of professional sports and fitness industry into fitness physical culture, educational process. Results. A computer program based on the MediaPipe system has been developed for automated assessment of the effectiveness of physical exercise based on biomechanical properties of motor action, taking into account individual proportions of the body, determining the load on key points of the body in order to obtain an optimal health effect. Conclusions. The prospects for using this program to optimize the methodology of health-improving physical education are discussed.
Keywords: computer technology; computer vision; computer program; physical education; physical exercise; automation; schoolchildren.
For Citation: Shriner B. A., Zhomin K. M. Application of Computer vision Technologies in Health-Improving Physical Education. Journal of Pedagogical Innovations, 2024,
no. 3 (75), pp. 122–135. (In Russ.) DOI: https://doi.org/10.15293/1812-9463.2403.11
Financing. The study was carried out within the framework of the project “Optimization of the methodology of physical fitness classes”, which is implemented with the financial support of the Ministry of Education of the Russian Federation within the framework of state task No. 073-03-2024-052 dated 18.01.2024.
References
1. Velmozhko N. I., Boyko A. A. Development of an algorithm for recognizing physical exercises. Physics and radioelectronics in medicine and ecology: proceedings of the
XIV International Scientific Conference. Book 2. Vladimir, 2020, pp. 94–99. (In Russian)
2. Germanov K. V., Krasnoperova T. V., Germanova A. A. Analysis of the use of computer vision in sports. Scientific notes of the University named after P. F. Lesgaft, 2023, no. 9 (223), pp. 100–105. (In Russian)
3. Ermakov A. V. Analysis of the movement in martial arts using the OpenCV “computer vision” libraries and the MediaPipe artificial intelligence framework. Martial arts and martial arts: science, practice, education: Materials of the VI All-Russian Scientific and Practical Conference with international participation (Moscow, October 14, 2021). Under the general editorship of Yu. L. Orlov, L. G. Ryzhkova. Moscow: Publishing House of the Russian State University of Physical Culture, Sports, Youth and Tourism, 2021, pp. 106–111. (In Russian)
4. Kiselev Yu. V., Bogomolov I. A., Rozaliev V. L., Baklan V. A. Analysis of approaches, methods and solutions for detecting human posture. Choosing a tool for the task of determining a personʼs emotional state by his pose. Modern science-intensive technologies, 2023, no. 6, pp. 41–47. (In Russian)
5. Kobernik P. S. The use of artificial intelligence in the field of sports to optimize the work of fitness applications. Young scientist, 2024, no. 15 (514), pp. 453–454. (In Russian)
6. Konopko E. A., Sidin M. G. Education and artificial intelligence: opportunities, limitations and prospects. Student science for the development of the information society: Materials of the XV All-Russian Scientific and Technical Conference with the invitation of foreign scientists. Stavropol: Publishing House of the North Caucasian Federal University, 2024, pp. 37–42. (In Russian)
7. Kulakov P. A., Eremin A. S. Features of the development of computer training simulators in Unity 3D. Izvestia Tula State University. Technical sciences, 2024, no. 1, pp. 177–181. (In Russian)
8. Mednikova E. V., Kotlyarov E. S., Popova M. V. Prospects for the use of artificial intelligence applications in physical education. Student sports: innovation, technology and digital transformation: materials of the I All-Russian Scientific and Practical Conference (Kaliningrad, March 30–31, 2023). Kaliningrad: Publishing House of the I. Kant Baltic Federal University, 2023, pp. 153–156. (In Russian)
9. Pyataeva A. V., Merko M. A., Zhukovskaya V. A., Kazakevich A. A. Recognition of human activity from video data. International Journal of Advanced Studies, 2022, vol. 12, issue 4, pp. 96–110. (In Russian)
10. Sivtsov I. V. The revolution of artificial intelligence in sports tourism: efficiency, safety and personalization. Problems and prospects for the development of orienteering and active types of tourism: Materials of the III All-Russian Scientific and Practical Conference with international participation. Smolensk: Publishing House of the Smolensk State University of Sports, 2024, pp. 222–224. (In Russian)
11. Terekhin A. D., Ilyalov O. R., Stepanov A. V. The system of estimation of sports exercises according to the neural network analysis of a video series. Applied mathematics and issues of management, 2022, no. 1, pp. 75–86. (In Russian)
12. Shilkina G. N. Application of innovative training technologies in the field of physical education at the university. Opportunities and prospects. Innovations in sports science: generational experience and new technologies: Materials of the All-Russian Scientific and Practical Conference with international participation. Moscow: Publishing House of the Russian University of Economics named after G. V. Plekhanov, 2024, pp. 219–223.
(In Russian)
13. Shriner B. A., Zhomin K. M. Innovative approaches in the organization of physical education with the use of computer technology. Journal of Pedagogical Innovations, 2023, no. 4 (72), pp. 77–85. (In Russian)
14. Moeslund T. B., Thomas G., Hilton A. Computer Vision in Sports. Advances in Computer Vision and Pattern Recognition [Electronic resource]. URL: https://link.springer.com/book/10.1007/978-3-319-09396-3#bibliographic-information (date of access: 17.04.2024).
15. Naik B. T., Hashmi M. F., Bokde N. D. A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions. Applied Sciences, 2022, vol. 12, issue 9. DOI: https://doi.org/10.3390/app12094429
16. Smith J., Johnson M. Exploring the applications of computer vision in sports [Electronic resource]. URL: https://www.ultralytics.com/blog/exploring-the-applications-of-computer-vision-in-sports (date of access: 17.04.2024).
Information about the Authors
Boris A. Schreiner – Candidate of Psychological Sciences, Associate Professor of the Department of Information Systems, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0002-5697-2701, boris.shrayner@gmail.com
Konstantin M. Zhomin – Candidate of Biological Sciences, Associate Professor, Associate Professor of the Department of Sports Disciplines, Novosibirsk State Pedagogical University, Novosibirsk, Russia, https://orcid.org/0000-0001-8642-9470, kos-jom83@mail.ru
Authorsʼ contribution: Authors have all made an equivalent contribution to preparing the article for publication.
The authors declare no conflict of interest.
