RF-CGR: Enable Chinese Character Gesture Recognition With RFID
Zhixiong Yang, Ziyi Zhen, Zijian Li, Xu Liu, Bo Yuan, Yajun Zhang · IEEE Transactions on Instrumentation and Measurement · 2023
Gesture recognition is the basis of human-computer interaction (HCI), and RFID has attracted wide attention for its advantages of lightweight, low cost, and universality. We propose RF-CGR, which implements cross-domain Chinese character gesture recognition intuitively and effectively. The fundamental concept of RF-CGR is to extract hand motion patterns from RFID phase information and display distinctive gesture features. Firstly, we build a signal sensing model to capture gesture information effectively. Secondly, we innovatively convert the Chinese character phase signal into an intuitive picture representation and use the gesture movement change pattern as input through data pre-processing operations. Finally, Modify-Visual Geometry Group Network (M-VGG) model is used for cross-domain gesture recognition. The M-VGG network learns high-level semantic features of gestures through spatiotemporal convolutions to extract cross-domain gesture features. Compared with other models, M-VGG has fewer parameters, and shorter training time, while still achieving high-accuracy gesture recognition. We evaluate its performance in three scenarios. The accuracy is 98.75% and 98% for new users and new scenarios respectively, significantly outperforming existing wireless signal-based gesture recognition methods.