Abstract
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.