运动中的追踪方法:对绩效数据的进步,质量和挑战的审查
Felipe Arruda Moura1, Fabio Giuliano Caetano1, Ricardo da Silva Torres2
1Sport Sciences Department, State University of Londrina, Londrina, Brazil.
International journal of sports medicine
|April 8, 2025
概括
运动员跟踪系统使用计算机视觉,人工智能和定位技术分析运动员的表现. 这次审查涵盖了系统基础,数据质量和准确体育分析的未来方向.
科学领域:
- 运动科学 运动科学 运动科学
- 绩效分析 绩效分析
- 生物机械工程 生物机械工程
背景情况:
- 运动员跟踪系统对于体育运动中的绩效分析至关重要.
- 这些系统的数据为训练和战术决策提供了信息.
- 系统的有效性因体育环境和特定要求而有所不同.
研究的目的:
- 审查主要运动员跟踪系统的基础知识.
- 讨论视频处理 (计算机视觉,AI) 的算法.
- 涵盖全球和地方定位系统和人类姿势估计.
主要方法:
- 科学文献的叙述性审查.
- 分析计算机视觉和人工智能算法.
- 检查全球定位系统 (GPS) 和全球导航卫星系统 (GNSS) 数据.
- 对局部定位系统和人类姿势估计技术的审查.
主要成果:
- 概述各种跟踪系统技术及其基本原则.
- 讨论数据采集的技术进步,包括人类姿势估计.
- 对不同跟踪方法的验证和质量分析研究的摘要.
结论:
- 准确的运动员跟踪对于体育领域的知情决策至关重要.
- 技术进步为性能分析提供了新的可能性.
- 为开发更好的追踪工具提供了建议和未来的方向.
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