AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale
Abstract
While reconstructing human poses in 3D from inexpensive sensors has advanced significantly in recent years, quantifying the dynamics of human motion, including the muscle-generated joint torques and external forces, remains a challenge. Prior attempts to estimate physics from reconstructed human poses have been hampered by a lack of datasets with high-quality pose and force data for a variety of movements. We present the AddBiomechanics Dataset 1.0, which includes physically accurate human dynamics of 273 human subjects, over 70 hours of motion and force plate data, totaling more than 24 million frames. To construct this dataset, novel analytical methods were required, which are also reported here. We propose a benchmark for estimating human dynamics from motion using this dataset, and present several baseline results. The AddBiomechanics Dataset is publicly available at addbiomechanics.org/download data.html.
Cite
Text
Werling et al. "AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale." Proceedings of the European Conference on Computer Vision (ECCV), 2024. doi:10.1007/978-3-031-73223-2_27Markdown
[Werling et al. "AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale." Proceedings of the European Conference on Computer Vision (ECCV), 2024.](https://mlanthology.org/eccv/2024/werling2024eccv-addbiomechanics/) doi:10.1007/978-3-031-73223-2_27BibTeX
@inproceedings{werling2024eccv-addbiomechanics,
title = {{AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale}},
author = {Werling, Keenon and Kaneda, Janelle M and Tan, Tian and Agarwal, Rishi and Skov, Six and Van Wouwe, Tom and Uhlrich, Scott and Delp, Scott and Liu, Karen and Bianco, Nicholas A and Ong, Carmichael and Falisse, Antoine and Sapkota, Shardul and Chandra, Aidan Jai and Carter, Joshua A and Preatoni, Ezio and Fregly, Benjamin J and Hicks, Jennifer},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
doi = {10.1007/978-3-031-73223-2_27},
url = {https://mlanthology.org/eccv/2024/werling2024eccv-addbiomechanics/}
}