English

CSI-Net: Unified Human Body Characterization and Pose Recognition

Machine Learning 2019-01-23 v2 Artificial Intelligence Machine Learning

Abstract

We build CSI-Net, a unified Deep Neural Network~(DNN), to learn the representation of WiFi signals. Using CSI-Net, we jointly solved two body characterization problems: biometrics estimation (including body fat, muscle, water, and bone rates) and person recognition. We also demonstrated the application of CSI-Net on two distinctive pose recognition tasks: the hand sign recognition (fine-scaled action of the hand) and falling detection (coarse-scaled motion of the body).

Keywords

Cite

@article{arxiv.1810.03064,
  title  = {CSI-Net: Unified Human Body Characterization and Pose Recognition},
  author = {Fei Wang and Jinsong Han and Shiyuan Zhang and Xu He and Dong Huang},
  journal= {arXiv preprint arXiv:1810.03064},
  year   = {2019}
}

Comments

14 pages, 6 figures and 10 tables

R2 v1 2026-06-23T04:30:50.772Z