Design of Basketball Teaching Aid System Based on Artificial Intelligence

被引：0

作者：

Xu X. ^{[1
]}

Wu H. ^{[1
]}

机构：

[1] Basic Education Department, Southeast University of Chengxian College, Jiangsu, Nanjing

来源：

Applied Mathematics and Nonlinear Sciences | 2024年 / 9卷 / 01期

关键词：

Artificial intelligence; Basketball teaching; Media pipe; SVM algorithm;

D O I：

10.2478/amns-2024-1608

中图分类号：

学科分类号：

摘要：

Artificial intelligence has penetrated every aspect of people's lives with the rapid development of science and technology. In basketball, how to effectively utilize artificial intelligence technology to improve the effectiveness of training has become a problem worth studying. A Mediapipe-based 3D human posture domain adaptive detection method is proposed in the study by combining statistics and human limb proportion simulation. The modified SVM classification algorithm is used to compare and classify the newly acquired key point data information of the system with the standard basketball action key point data information preset by the system to judge whether the basketball action is up to the standard or not, so as to design the basketball teaching aid system based on artificial intelligence. Based on this basis, after testing the recognition performance of the system, its practical application effect is explored. The total basketball scores improved after the experiment (86.26±2.228 for the experimental group and 81.34±9.672 for the control group), but there was no significant difference (P>0.05). The control group was slower than the experimental group by 0.64 seconds and 0.77 seconds overall in the cross-step breakout time with the ball and the same-side step breakout time with the ball, respectively, indicating that the experimental group was more proficient in basketball technology. The system has been tested in various ways to meet the multiple needs of the users, meet the expected standards, and be able to be applied in real-world scenarios. © 2024 Xiaohu Xu et al., published by Sciendo.

引用

共 20 条

[1]

Bo Q., The sustainable development of psychological education in students’ learning concept in physical education based on machine learning and the internet of things, Sustainability, 14, (2022)

[2]

Grsten A., Yli-Piipari S., Huhtiniemi M., Salin K., Hakonen H., Jaakkola T., A one-year follow-up of basic psychological need satisfactions in physical education and associated in-class and total physical activity, European Physical Education Review, 27, 3, pp. 436-454, (2021)

[3]

Zanon F., Marcantoni L., Pastore G., Baracca E., Roncon L., The challenge of education in conduction system pacing: results from single or dual operators, European Heart Journal, 41, (2020)

[4]

Carse N., Jess M., Keay J., Start young: the possibilities of primary physical education, European Physical Education Review, (2017)

[5]

Lohmann J., Goller A., Physical education teacher educators’ subjective theories about sustainability and education for sustainable development, International Journal of Sustainability in Higher Education, 24, 4, pp. 877-894, (2023)

[6]

Hu Y., Xu Y., Study on the automatic basketball shooting system based on the background subtraction method, Scientific programming, (2021)

[7]

Shi F., Hu X., Fuzzy dynamic obstacle avoidance algorithm for basketball robot based on multi-sensor data fusion technology, International Journal of Foundations of Computer Science, (2022)

[8]

Mulrey C.R., Shultz S.J., Ford K.R., Nguyen A.D., Taylor J.B., Methods of identifying limb dominance in adolescent female basketball players, Clinical Journal of Sport Medicine, (2018)

[9]

Liu R., Liu Z., Liu S., Recognition of basketball player’s shooting action based on the convolutional neural network, Scientific Programming, (2021)

[10]

Guo Q., Li B., Role of ai physical education based on application of functional sports training, Journal of Intelligent and Fuzzy Systems, 2, pp. 1-9, (2020)

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