Chromy Adam, Sopak Petr, Cigler Hynek
CEITEC-Central European Institute of Technology, Brno University of Technology, Purkynova 656/123, 612 00, Brno, Czech Republic.
Faculty of Electrical Engineering and Communications, Brno University of Technology, Technicka 3082/12, 616 00, Brno, Czech Republic.
Sci Rep. 2025 Jul 2;15(1):23351. doi: 10.1038/s41598-025-06111-9.
Motion Capture (MoCap) is rapidly growing in the sports, biomechanics, healthcare, and medicine segments, where accuracy is crucial. Current research studies are concurrently confirming that the accuracy can be determined only for the specific analyzed configuration and thus recommending performing your own accuracy verification on your specific setup. However, it is often hard to perform since it requires significant effort, time, knowledge of statistical data analysis and often equipment and tools that are not commonly available. This paper deals with this by creating a standardized setup with carefully evaluated accuracy, substituting the on-site validation process (in case of using such a setup) or providing the worst-case accuracy (when a more advanced setup is used). The setup is designed to be low-cost, easily reproducible and cover a wide range of applications - thus VICON setup with five VERO v1.3 cameras is used. The accuracy was evaluated using the robotic manipulator EPSON C3, determining that the absolute positioning accuracy of such a standardized setup is 0.65 mm on average (SD = 0.48, with maximal error of 2.47 mm) and rotation accuracy 0.40° (SD = 0.35, with maximal error of 2.0°), which is negligible considering the experimental diameter of 1.4 m and full angular span. The major source of error was specific to particular spatial and rotational positions; other systematic and other random errors were noticeably smaller. If the standardized setup is used and all its requirements are met, a similar accuracy as validated above can be expected without the need to explicitly validate the specific configuration, which is time-consuming and resource-intensive.
动作捕捉(MoCap)在体育、生物力学、医疗保健和医学领域正迅速发展,在这些领域中精度至关重要。当前的研究同时证实,只能针对特定的分析配置确定精度,因此建议针对您的特定设置进行自己的精度验证。然而,这通常很难进行,因为它需要大量的精力、时间、统计数据分析知识,而且通常还需要不常见的设备和工具。本文通过创建一个经过精心评估精度的标准化设置来解决这个问题,替代现场验证过程(如果使用这样的设置)或提供最坏情况下的精度(当使用更先进的设置时)。该设置旨在低成本、易于重现并涵盖广泛的应用——因此使用了配备五个VERO v1.3相机的VICON设置。使用爱普生C3机器人操纵器评估精度,确定这种标准化设置的绝对定位精度平均为0.65毫米(标准差=0.48,最大误差为2.47毫米),旋转精度为0.40°(标准差=0.35,最大误差为2.0°),考虑到1.4米的实验直径和全角跨度,这是可以忽略不计的。误差的主要来源特定于特定的空间和旋转位置;其他系统误差和其他随机误差明显较小。如果使用标准化设置并满足其所有要求,则无需明确验证特定配置即可预期获得与上述验证相似的精度,而明确验证特定配置既耗时又耗费资源。