Koul Atesh, Novembre Giacomo
Neuroscience of Perception and Action Lab, Italian Institute of Technology (IIT), Viale Regina Elena 291, 00161, Rome, Italy.
Behav Res Methods. 2025 Jan 2;57(1):38. doi: 10.3758/s13428-024-02546-6.
Estimating how the human body moves in space and time-body kinematics-has important applications for industry, healthcare, and several research fields. Gold-standard methodologies capturing body kinematics are expensive and impractical for naturalistic recordings as they rely on infrared-reflective wearables and bulky instrumentation. To overcome these limitations, several algorithms have been developed to extract body kinematics from plain video recordings. This comes with a drop in accuracy, which however has not been clearly quantified. To fill this knowledge gap, we analysed a dataset comprising 46 human participants exhibiting spontaneous movements of varying amplitude. Body kinematics were estimated using OpenPose (video-based) and Vicon (infrared-based) motion capture systems simultaneously. OpenPose accuracy was assessed using Vicon estimates as ground truth. We report that OpenPose accuracy is overall moderate and varies substantially across participants and body parts. This is explained by variability in movement amplitude. OpenPose estimates are weak for low-amplitude movements. Conversely, large-amplitude movements (i.e., > ~ 10 cm) yield highly accurate estimates. The relationship between accuracy and movement amplitude is not linear (but mostly exponential or power) and relatively robust to camera-body distance. Together, these results dissect the limits of video-based motion capture and provide useful guidelines for future studies.
估算人体在空间和时间中的运动方式——身体运动学——在工业、医疗保健以及多个研究领域都有重要应用。用于捕捉身体运动学的金标准方法成本高昂,且对于自然主义记录而言不切实际,因为它们依赖于红外反射式可穿戴设备和笨重的仪器。为克服这些限制,人们开发了多种算法,用于从普通视频记录中提取身体运动学信息。这会导致精度下降,然而精度下降的程度尚未得到明确量化。为填补这一知识空白,我们分析了一个包含46名人类参与者的数据集,这些参与者展示了不同幅度的自发运动。同时使用OpenPose(基于视频)和Vicon(基于红外)运动捕捉系统估算身体运动学信息。以Vicon估算值作为基准真值来评估OpenPose的精度。我们报告称,OpenPose的精度总体适中,且在不同参与者和身体部位之间存在很大差异。这可以通过运动幅度的变化来解释。OpenPose对低幅度运动的估算效果较差。相反,大幅度运动(即大于约10厘米)能产生高度准确的估算结果。精度与运动幅度之间的关系不是线性的(但大多呈指数或幂函数关系),并且对相机与身体的距离相对不敏感。总之,这些结果剖析了基于视频的运动捕捉的局限性,并为未来的研究提供了有用的指导方针。