Zheng Wen, Zhang Mingxin, Dong Rui, Qiu Mingjia, Wang Wei
School of Athletic Performance, Shanghai University of Sport, Shanghai 200438, China.
Shanghai Key Lab of Human Performance, Shanghai University of Sport, Shanghai 200438, China.
Sensors (Basel). 2025 Jun 27;25(13):4003. doi: 10.3390/s25134003.
Markerless motion capture (MMC) offers a non-invasive method for monitoring external load in sports where wearable devices are restricted; however, its validity in 3x3 basketball contexts remains unverified. The viability and measurement precision of a multi-camera RTMPose-based MMC system for single-player tasks in 3x3 basketball performance monitoring were evaluated in this study. Recorded on a standard half-court, eight cameras (60 fps) captured ten collegiate athletes executing basketball-specific activities including linear sprints, curved runs, T-tests, and vertical jumps. The 3D coordinates of hip and ankle keypoints were reconstructed from multiple synchronized camera views using Direct Linear Transformation (DLT), from which horizontal displacement and average speed were derived. These values were validated using tape-measure distance and time-motion analysis. The MMC system demonstrated high accuracy, with coefficients of variation (CVs) below 5%, mean bias under 3.5%, and standard error of estimate (SEE) below 3% across most tasks. Speed estimates revealed great consistency with time-motion analysis (ICC = 0.97-1.00; standardized change in mean [SCM] varied from trivial to small). The Bland-Altman graphs verified no proportional error and little bias. These results confirm the MMC system as a consistent, non-invasive method for gathering movement data in outdoor basketball environments. Future studies should assess the system's performance during live competitive play with several athletes and occlusions and compare it to a laboratory-grade motion capture system.
无标记运动捕捉（MMC）提供了一种非侵入性方法，用于在可穿戴设备受限的运动中监测外部负荷；然而，其在3x3篮球场景中的有效性仍未得到验证。本研究评估了基于多摄像头RTMPose的MMC系统在3x3篮球性能监测中用于单人任务的可行性和测量精度。在标准半场进行记录，八个摄像头（60帧/秒）捕捉了十名大学生运动员执行篮球特定活动，包括直线冲刺、曲线跑、T型测试和垂直跳跃。使用直接线性变换（DLT）从多个同步摄像头视图重建髋部和脚踝关键点的三维坐标，并从中得出水平位移和平均速度。这些值通过卷尺测量距离和时间-动作分析进行验证。MMC系统显示出高精度，在大多数任务中变异系数（CV）低于5%，平均偏差低于3.5%，估计标准误差（SEE）低于3%。速度估计与时间-动作分析显示出高度一致性（组内相关系数[ICC]=0.97-1.00；平均标准化变化[SCM]从微不足道到较小不等）。布兰德-奥特曼图验证了无比例误差且偏差很小。这些结果证实了MMC系统是一种在户外篮球环境中收集运动数据的一致、非侵入性方法。未来的研究应评估该系统在有多名运动员和遮挡的现场比赛中的性能，并将其与实验室级运动捕捉系统进行比较。
