摄像头视角对OpenPose在运动分析中的有效性的影响
Melanie Baldinger1, Lara Marie Reimer2, Veit Senner1
1School of Engineering and Design, Technical University of Munich, 85748 Garching b. Munich, Germany.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
人体姿势估计 (HPE) 算法在生物力学方面表现有前途,但需要在实验室外进行验证. 后视摄像头通常通过OpenPose产生最准确的关节角度估计,最大限度地减少偏差.
科学领域:
- 生物力学 生物力学
- 计算机视觉 计算机视觉
- 人类运动分析分析
背景情况:
- 人体姿势估计 (HPE) 在生物力学中越来越多地被使用.
- 在受控实验室环境之外,关于HPE算法的适用性存在有限的研究.
- 调查非标准摄像头设置对HPE有效性的影响至关重要.
研究的目的:
- 量化不同摄像头视角对人类姿势估计准确度的影响.
- 使用OpenPose与黄金标准相比,评估联合角度估计的有效性.
- 在生物力学分析中确定最佳的摄像头设置以获得可靠的HPE.
主要方法:
- 视频数据从四个不同的摄像头角度捕获.
- 通过使用OpenPose软件提取关键点.
- 估计的动力学数据与基于标记器的运动捕捉黄金标准系统进行了比较.
- 对膝盖,部,肘部和肩部关节角度的准确性进行了评估.
主要成果:
- 在大多数关节角度 (不包括肩膀) 中,OpenPose与黄金标准有合理的相关性.
- 在不同摄像头视角的联合角度估计中观察到显著的偏差.
- 后视摄像头角度通常提供最好的性能与最低的百分比偏差.
结论:
- 摄像机的视角显著影响生物力学中人类姿势估计的准确性.
- 后视视角的视角似乎是最可靠的联合角度估计.
- 对特定的摄像头设置进行彻底的验证对于HPE的各种现实应用至关重要.
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