Original article
DOI: 10.15293/1812-9463.2304.06
Boris A. Shriner
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Konstantin M. Zhomin
Novosibirsk State Pedagogical University, Novosibirsk, Russia
Abstract. The article examines the prospects for using computer vision technologies in the process of physical education of schoolchildren. Modern methods of pattern recognition, detection and tracking of objects are analyzed, which can be used for automated control over the performance of physical exercises. Particular attention is paid to the capabilities of the MediaPipe library, which allows you to track the position and movement of human body parts in real time. We considered specific algorithms and software solutions based on MediaPipe, OpenCV, TensorFlow, Keras, which allow you to analyze the correctness of movement, assess physical activity, and recognize errors. The possibility of using neural network algorithms to assess posture and build an optimal trajectory of movements is shown. The CV-Trainer program was developed and tested for automated assessment of constitutional features (body type), determination of body proportions, calculation of angles and lengths of body segments, which allows you to quantify the amplitude and trajectory of motion of motor action on video. The prospects of integrating computer vision technologies into the educational process to increase the efficiency and individualization of physical education of schoolchildren are discussed.
Keywords: computer technology, computer vision, computer program, physical education, physical exercise, automation, schoolchildren.
For Citation: Shriner B. A., Zhomin K. M. Innovative Approaches in Organizing Physical Education Classes Using Computer Technologies. Journal of Pedagogical Innovations, 2023, no. 4 (72), pp. 77–85. (In Russ.) DOI: https://doi.org/10.15293/1812-9463.2304.06
Funding. The study was carried out within the framework of the project “Research and development of methods for classes on recreational physical educationˮ, which is being implemented with the financial support of the Ministry of Education of the Russian Federation within the framework of state task no. 073-03-2023-027 of 27.01.2023.
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Information about the Authors
Boris А. 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.
Received: 18.08.2023; approved after peer review: 18.10.2023; accepted for publication: 02.11.2023.