AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale.

Keenon Werling, Janelle Kaneda, Tian Tan, Rishi Agarwal, Six Skov, Tom Van Wouwe, Scott Uhlrich, Nicholas Bianco, Carmichael Ong, Antoine Falisse, Shardul Sapkota, Aidan Chandra, Joshua Carter, Ezio Preatoni, Benjamin Fregly, Jennifer Hicks, Scott Delp, C Karen Liu
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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.

添加生物力学数据集:大规模捕获人体运动的物理。
虽然近年来通过廉价的传感器在3D中重建人体姿势取得了显着进展,但量化人体运动的动力学,包括肌肉产生的关节扭矩和外力,仍然是一个挑战。由于缺乏各种运动的高质量姿势和力数据集,先前从重建的人体姿势估计物理的尝试受到阻碍。我们提出了AddBiomechanics Dataset 1.0,其中包括273人的物理精确的人体动力学,超过70小时的运动和力板数据,总计超过2400万帧。为了构建这个数据集,需要新的分析方法,这里也有报道。我们提出了一个使用该数据集从运动中估计人类动力学的基准,并提出了几个基线结果。AddBiomechanics数据集可在addbiomechanics.org/download_data.html公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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