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Human Sensing Using Visible Light Communication

Li, Tianxing, An, Chuankai, Tian, Zhao, Campbell, Andrew T., Zhou, Xia·2015·Proceedings of the 21st Annual International Conference on Mobile Computing and Networking

Abstract

We present LiSense, the first-of-its-kind system that enables both data communication and fine-grained, real-time human skeleton reconstruction using Visible Light Communication (VLC). LiSense uses shadows created by the human body from blocked light and reconstructs 3D human skeleton postures in real time. We overcome two key challenges to realize shadow-based human sensing. First, multiple lights on the ceiling lead to diminished and complex shadow patterns on the floor. We design light beacons enabled by VLC to separate light rays from different light sources and recover the shadow pattern cast by each individual light. Second, we design an efficient inference algorithm to reconstruct user postures using 2D shadow information with a limited resolution collected by photodiodes embedded in the floor. We build a 3 m x 3 m LiSense testbed using off-the-shelf LEDs and photodiodes. Experiments show that LiSense reconstructs the 3D user skeleton at 60 Hz in real time with 10 degrees mean angular error for five body joints.

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Metadata

Authors
Li, T., An, C., Tian, Z., Campbell, A. T., & Zhou, X.
Venue
Proceedings of the 21st Annual International Conference on Mobile Computing and Networking
Publisher
ACM
Published
2015-09-07
Pages
331-344
ISSN
1543-5679 (ISSN-L)
OpenAlex
W2050304483
Cited by
240
References
0
FWCI
34.36
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Human Sensing Using Visible Light Communication. https://app.cochat.ai/papers/10.1145/2789168.2790110
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Li, T., An, C., Tian, Z., Campbell, A. T., & Zhou, X. (2015). Human Sensing Using Visible Light Communication. Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. https://doi.org/10.1145/2789168.2790110

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