3D Human Pose Estimation for Free-from and Moving Activities Using WiFi

This paper presents GoPose, a 3D skeleton-based human pose estimation system that uses commodity WiFi devices at home. Our system leverages the WiFi signals reflected off the human body for 3D pose estimation. In contrast to prior systems that need dedicated sensors, our system does not require a user to wear any sensors and can reuse the WiFi devices that already exist in a home environment for mass adoption. To realize such a system, we leverage the 2D AoA estimation of the signals reflected from the human body and the deep learning techniques. Preliminary results show GoPose achieves a high accuracy of 4.5cm in various scenarios.