Comparative analysis of functional and core strength training on developing basketball skills using intelligent feature recognition

To explore the effective training strategies of college students’ basketball special ability, this paper conducts a comparative study of functional training and core strength training on college students’ basketball special ability training through intelligent methods. Moreover, this study integrates monocular visual SLAM and LSD-SLAM algorithms into the training method through intelligent methods. Monocular visual SLAM is used to achieve 3D point cloud reconstruction based on LSD-SLAM algorithm, combined with basketball training features to construct an intelligent recognition system. The LSD-SLAM algorithm is used in training to accurately track athlete movements, provide depth information, optimize posture estimation, and assist in functional training and core strength training. The two work together to enhance college basketball specific abilities. The results show that both functional training and core strength training have certain effects on the cultivation of the college students’ basketball special ability, so it is necessary to combine the two to improve the college students’ basketball special ability.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-08-12
DOI
https://doi.org/10.1177/14727978251366538
Primary Topic
AI and Multimedia in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparative analysis of functional and core strength training on developing basketball skills using intelligent feature recognition

Zhenguo Liu
1 links
Journal of Computational Methods in Sciences and Engineering
AI and Multimedia in Education
article

Comparative analysis of functional and core strength training on developing basketball skills using intelligent feature recognition

Zhenguo Liu
article en

Abstract

To explore the effective training strategies of college students’ basketball special ability, this paper conducts a comparative study of functional training and core strength training on college students’ basketball special ability training through intelligent methods. Moreover, this study integrates monocular visual SLAM and LSD-SLAM algorithms into the training method through intelligent methods. Monocular visual SLAM is used to achieve 3D point cloud reconstruction based on LSD-SLAM algorithm, combined with basketball training features to construct an intelligent recognition system. The LSD-SLAM algorithm is used in training to accurately track athlete movements, provide depth information, optimize posture estimation, and assist in functional training and core strength training. The two work together to enhance college basketball specific abilities. The results show that both functional training and core strength training have certain effects on the cultivation of the college students’ basketball special ability, so it is necessary to combine the two to improve the college students’ basketball special ability.

Journal of Computational Methods in Sciences and Engineering
Shenyang Sport University (CN)
Openalex Percentile: Top 89%
AI and Multimedia in Education
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