GoPose: A 3D Skeleton-Based Human Pose Estimation System Using WiFi Signals
3D Human Pose Estimation for Free-from and Moving Activities Using WiFi
This paper presents a 3d skeleton-based human pose estimation system that uses wifi devices at home for mass adoption.Our system leverages the wifi signals reflected off the human body for 3d pose estimation.In contrast to prior systems that need specialized hardware or dedicated sensors, our system does not require a user to wear or carry any sensors and can reuse the wifi devices that already exist in a home environment for mass adoption.Deep learning is incorporated to model the complex relationship between the 2d antenna array (2d aoa) spectrum of the signals reflected from the human body and the 3d skeletons of the human body for pose tracking.Evaluation results show that our system achieves around 4.7cm of accuracy under various scenarios including tracking unseenactivities and under nlos scenarios.
