This work presents StarLight, an infrastructure-based sensing system that reuses light emitted from ceiling LED panels to reconstruct fine-grained user skeleton postures continuously in real time. It relies on only a few (e.g., 20) photodiodes placed at optimized locations to passively capture low-level visual clues (light blockage information), with neither cameras capturing sensitive images, nor on-body devices, nor electromagnetic interference. It then aggregates the blockage information of a large number of light rays from LED panels and identifies best-fit 3D skeleton postures. StarLight greatly advances the prior light-based sensing design by dramatically reducing the number of intrusive sensors, overcoming furniture blockage, and supporting user mobility. StarLight is deployed in a 3.6 m x 4.8 m office room, with customized 20 LED panels and 20 photodiodes. Experiments show that StarLight achieves 13.6° mean angular error for five body joints and reconstructs a mobile skeleton at a high frame rate (40 FPS). StarLight enables a new unobtrusive sensing paradigm to augment today’s mobile sensing for continuous and accurate behavioral monitoring.

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