Image: Jiaqi Geng, Dong Huang, Fernando De la Torre
Researchers at Carnegie Mellon University have developed a WiFi based human pose sensing system that can identify multiple people and their positions in a room using the phase and amplitude of the WiFi signal, filtered using machine learning models. The system can map the UV coordinates of body regions and is comparable to image based recognition systems.
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