A WiFi-based perception system that converts invisible WiFi signal reflections (CSI) into human pose estimates and vital sign analytics. The project features a dual-mode architecture: a DensePose pipeline that uses deep learning to map body coordinates for general tracking, and a WiFi-Mat disaster response module designed to detect breathing and heartbeats of survivors trapped in rubble.
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A WiFi-based perception system that converts invisible WiFi signal reflections (CSI) into human pose estimates and vital sign analytics. The project features a dual-mode architecture: a DensePose pipeline that uses deep learning to map body coordinates for general tracking, and a WiFi-Mat disaster response module designed to detect breathing and heartbeats of survivors trapped in rubble.
Source Repository: https://github.com/ruvnet/wifi-densepose
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