AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale
Keenon Werling*, Janelle M Kaneda, Tian Tan, Rishi Agarwal, Six Skov, Tom Van Wouwe, Scott Uhlrich, Scott Delp
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."
BibTeX
@inproceedings{eccv2024_addbiomechanicsd,
title = {AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale},
author = {Keenon Werling* and Janelle M Kaneda and Tian Tan and Rishi Agarwal and Six Skov and Tom Van Wouwe and Scott Uhlrich and Scott Delp and Karen Liu and Nicholas A Bianco and Carmichael Ong and Antoine Falisse and Shardul Sapkota and Aidan Jai Chandra and Joshua A Carter and Ezio Preatoni and Benjamin J Fregly and Jennifer Hicks},
booktitle = {ECCV 2024},
year = {2024}
}