# Fast and scalable human pose estimation using mmWave point cloud

@article{An2022FastAS,
title={Fast and scalable human pose estimation using mmWave point cloud},
author={Sizhe An and Umit Y. Ogras},
journal={Proceedings of the 59th ACM/IEEE Design Automation Conference},
year={2022}
}
• Published 29 April 2022
• Computer Science
• Proceedings of the 59th ACM/IEEE Design Automation Conference
Millimeter-Wave (mmWave) radar can enable high-resolution human pose estimation with low cost and computational requirements. However, mmWave data point cloud, the primary input to processing algorithms, is highly sparse and carries significantly less information than other alternatives such as video frames. Furthermore, the scarce labeled mmWave data impedes the development of machine learning (ML) models that can generalize to unseen scenarios. We propose a fast and scalable human pose…
1 Citations

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