CSI-Net: Unified Human Body Characterization and Pose Recognition
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Abstract (arXiv)
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).
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Oct 2018.
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3 papers.