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使用单个未校准的摄像头对反运动跳跃性能进行自动视频分析
Chuang-Yuan Chiu1, Chien-Chun Chang2, Yi-Chien Chiang3
1Sports Engineering Research Group, Sport and Physical Activity Research Centre, Sheffield Hallam University, Sheffield, UK.
Journal of biomechanics
|April 25, 2025
概括
一个新的基于摄像头的系统使用计算机视觉和生物力学自动分析反运动跳跃 (CMJ) 性能. 这种具有成本效益的方法提供了准确,可靠的体育表现数据,无需专门的设备或专业知识.
科学领域:
- 生物力学 生物力学
- 体育科学 运动科学 运动科学
- 计算机视觉 计算机视觉
背景情况:
- 反运动跳跃 (CMJ) 评估对于体育表现监测至关重要.
- 使用强力板的传统方法昂贵且繁.
- 现有的IMU和移动应用解决方案需要技术专长和手动输入.
研究的目的:
- 开发一个自动化的,基于摄像头的管道,用于CMJ性能分析.
- 利用计算机视觉和生物力学原理来准确地提取数据.
- 为现有CMJ评估工具提供一个成本效益和用户友好的替代方案.
主要方法:
- 采用单摄像头视频的人类细分和姿势估计.
- 应用生物力学原理 (抛物线运动,反向动力学) 来估计力-时间数据.
- 验证了系统与77名精英运动员的商业力量平台相比.
主要成果:
- 对大多数CMJ变量实现了优异的相关性 (R > 0.7) 和高可靠性 (%CV < 10%).
- 证明了力-时间数据和性能变量的全自动分析.
- 在准确性和可靠性方面超越了基于IMU的方法.
结论:
- 开发的基于摄像头的方法提供了自动化,准确和可靠的CMJ分析.
- 它减少了技术需求,提供了比移动应用程序更多的变量.
- 理想适用于大规模研究,增强体育表现和健康监测.
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