In-Bed Pressure-Based Pose Estimation Using Image Space Representation Learning

@article{Davoodnia2021InBedPP,
  title={In-Bed Pressure-Based Pose Estimation Using Image Space Representation Learning},
  author={Vandad Davoodnia and Saeed Ghorbani and Ali Etemad},
  journal={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2021},
  pages={3965-3969}
}
Recent advances in deep pose estimation models have proven to be effective in a wide range of applications such as health monitoring, sports, animations, and robotics. However, pose estimation models fail to generalize when facing images acquired from in-bed pressure sensing systems. In this paper, we address this challenge by presenting a novel end-to-end framework capable of accurately locating body parts from vague pressure data. Our method exploits the idea of equip-ping an off-the-shelf… Expand
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