Meta-Pose: Environment-adaptive Human Skeleton Tracking with RFID
Chao Yang, Lingxiao Wang, Xuyu Wang, Shiwen Mao · 2021 IEEE Global Communications Conference (GLOBECOM) · 2021
Human pose tracking has attracted great interest re-cently. Considerable efforts have been made in Radio-Frequency (RF) sensing techniques for human pose tracking without using a video camera. Although the existing RF based schemes can well protect user privacy, they are usually sensitive to the RF environment and are hard to generalize to new environments. In this paper, we analyze the challenges of generalization of Radio-Frequency Identification (RFID) based human pose tracking systems. We then present an RFID based 3D human pose tracking system, termed Meta-Pose, which incorporates meta-learning and few-shot fine-tuning to achieve high adaptability to new environments. The proposed system is implemented with commodity RFID devices and extensive experiments are conducted for performance evaluation. The experiment results validate the superior human pose tracking performance and high adaptability of the proposed Meta-Pose system.