mmPose-NLP: A Natural Language Processing Approach to Precise Skeletal Pose Estimation using mmWave Radars
A. Sengupta, S. Cao
IEEE Transactions on Neural Networks and Learning Systems, 2023 , Vol. 34 (11) , pp. 8418-8429
Abstract
This work introduces mmPose-NLP, applying natural language processing concepts to radar-based pose estimation. The approach treats radar point clouds as sequential data, enabling more effective temporal modeling and improved pose tracking accuracy. First method to precisely estimate up to 25 skeletal key points using mmWave radar data alone.
Citation
A. Sengupta, S. Cao. "mmPose-NLP: A Natural Language Processing Approach to Precise Skeletal Pose Estimation using mmWave Radars." IEEE Transactions on Neural Networks and Learning Systems 34(11): 8418-8429, 2023. DOI: 10.1109/TNNLS.2022.3151101
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Details
- Year
- 2023
- Published In
- IEEE Transactions on Neural Networks and Learning Systems
- Volume
- 34
- Issue
- 11
- Pages
- 8418-8429
- DOI
- 10.1109/TNNLS.2022.3151101