Performance Evaluation of Markerless 3D Skeleton Pose Estimates with Pop Dance Motion Sequence
The evaluation of markerless pose estimation performed by OpenPose has been getting much attention from researchers of human movement studies. This work aims to evaluate and compare the output joint positions estimated by the OpenPose with a marker-based motion-capture data recorded on a pop dance motion. Although the marker-based motion capture can accurately measure and record the human joint positions, this particular set-up is expensive. The framework to compare the outputs of the markerless method to the ground truth marker-based joint remains unknown, especially for complex body motion. Synchronization, camera calibration, and 3D reconstruction by fusing the outputs of the markerless method (OpenPose) are discussed. In this case study, the comparison results illustrate that the mean absolute errors for each key points are less than 700 mm. Contribution: This work contributes for human movement science by evaluating the OpenPose markerless 3D reconstruction pose with the marker-based motion-capture data recorded on pop dance motion.
Labuguen, R. T., Negrete, S. B., Kogami, T., Ingco, W. E. M., & Shibata, T. (2020). Performance evaluation of markerless 3D skeleton pose estimates with pop dance motion sequence. 2020 Joint 9th International Conference on Informatics, Electronics Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision Pattern Recognition (IcIVPR), 1–7. https://doi.org/10.1109/ICIEVicIVPR48672.2020.9306581