从田径广播中提取空间知识,用于单眼3D人体姿势估计
Tobias Baumgartner1, Benjamin Paassen2, Stefanie Klatt3
1Institute for Exercise Training and Sport Informatics, German Sport University, Cologne, Germany. t.baumgartner@dshs-koeln.de.
Scientific reports
|August 28, 2023
概括
收集人类运动数据是昂贵的. 虽然3D姿势估计显示了从广播中分析运行动力学的前景,但目前的方法缺乏生物力学研究所需的精度.
科学领域:
- 生物力学 生物力学
- 计算机视觉 计算机视觉
- 运动科学 运动科学 运动科学
背景情况:
- 大规模的人类移动数据收集是昂贵和耗时的.
- 在3D人体姿势估计方面的进步为分析从电视广播等不受约束的来源的运动提供了潜力.
- 精确的生物力学动力学分析需要高精度,错误率小于运动员之间的差异.
研究的目的:
- 评估使用当前3D人体姿势估计技术从广播镜头运行动力学分析的可行性.
- 提出一种从车道标记中推断体育场几何学的方法,以帮助3D姿势投影.
- 为了确定最先进的姿势估计是否足够准确,用于生物力学研究.
主要方法:
- 开发了一种方法来推断全球体育场的几何学使用车道标记在田径记录.
- 使用推断的几何学来预测估计的3D人类骨回到图像空间.
- 评估了与生物力学研究要求相对应的投影3D姿势的准确性.
主要成果:
- 当前最先进的3D人体姿势估计方法表明,对于精确的运行动力学研究来说,准确性不足.
- 推断体育场几何学的拟议方法有助于重新投影3D姿势,但无法克服基本的姿势估计限制.
- 在估计的3D连接角度的精度中观察到显著的差异.
结论:
- 尽管有改进,3D人类姿势估计技术尚未成熟,无法从广播数据中对运行动力学进行可靠的生物机械分析.
- 需要在姿势估计准确性方面取得进一步的进步,才能实际应用到使用无约束视频的体育科学和生物力学研究中.
- 目前的姿势估计误差和区分微妙生物力学差异所需的精度之间的差距仍然很大.
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