A Low-Cost & Real-Time Motion Capture System
Abstract
Traditional marker-based motion capture requires excessive and specialized equipment, hindering accessibility and wider adoption. In this work, we demonstrate such a system but rely on a very sparse set of low-cost consumer-grade sensors. Our system exploits a data-driven backend to infer the captured subject's joint positions from noisy marker estimates in real-time. In addition to reduced costs and portability, its inherent denoising nature allows for quicker captures by alleviating the need for precise marker placement and post-processing, making it suitable for interactive virtual reality applications.
Cite
Text
Chatzitofis et al. "A Low-Cost & Real-Time Motion Capture System." Conference on Computer Vision and Pattern Recognition, 2022.Markdown
[Chatzitofis et al. "A Low-Cost & Real-Time Motion Capture System." Conference on Computer Vision and Pattern Recognition, 2022.](https://mlanthology.org/cvpr/2022/chatzitofis2022cvpr-lowcost/)BibTeX
@inproceedings{chatzitofis2022cvpr-lowcost,
title = {{A Low-Cost & Real-Time Motion Capture System}},
author = {Chatzitofis, Anargyros and Albanis, Georgios and Zioulis, Nikolaos and Thermos, Spyridon},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2022},
pages = {21453-21458},
url = {https://mlanthology.org/cvpr/2022/chatzitofis2022cvpr-lowcost/}
}