Privacy-Preserving Gesture Tracking System Utilizing Frequency-Hopping RFID Signals
Bojun Zhang
TL;DR
The study tackles privacy concerns in gesture tracking by introducing a frequency-hopping RFID system that protects user data while maintaining real-time accuracy. A Conformer-based signal-generation model recovers original RFID signals from hopped inputs, enabling reliable gesture tracking with RSSI as auxiliary supervision. The approach combines a two-stage initialization via phase-difference confidence $V$ and multi-antenna trajectory tracking, validated on hardware with comparisons to SVM, MLP, and CNN baselines, and reinforced by ablations showing CNN and Transformer components are crucial. The results demonstrate robust, privacy-preserving gesture sensing suitable for smart homes and HCI applications, offering a viable path toward privacy-aware RFID-based sensing.
Abstract
Gesture tracking technology provides users with a hands free interactive experience without the need to hold or touch devices. However, current gesture tracking research has primarily focused on tracking accuracy while neglecting issues of user privacy protection and security. This study aims to develop a gesture tracking system based on frequency hopping RFID signals that effectively protects user privacy without compromising tracking efficiency and accuracy. By introducing frequency hopping technology, we have designed a mechanism that prevents potential eavesdroppers from obtaining raw RFID signals, thereby enhancing the systems privacy protection capabilities. The system architec ture includes the collection of RFID signals, data processing, signal recovery, and gesture tracking. Experimental results show that our method significantly improves privacy protection levels while maintaining real time and accuracy. This research not only provides a new perspective for the field of gesture tracking but also offers valuable insights for the use of RFID technology in privacy-sensitive applications.