ZTE Communications ›› 2021, Vol. 19 ›› Issue (3): 13-21.doi: 10.12142/ZTECOM.202103003

• Special Topic • Previous Articles     Next Articles

Device-Free In-Air Gesture Recognition Based on RFID Tag Array

WU Jiaying, WANG Chuyu(), XIE Lei   

  1. State Key Laboratory for Novel Software Technology, Nanjing 210023, China
  • Received:2021-06-10 Online:2021-09-25 Published:2021-10-11
  • About author:WU Jiaying is a Ph.D. student in the Department of Computer Science and Technology, Nanjing University, China, supervised by Prof. XIE Lei and WANG Chuyu. Her research interests include smart sensing and RFID.|WANG Chuyu (chuyu@nju.edu.cn) received his Ph.D. degree in computer science from Nanjing University, China in 2018. He is an assistant professor in the Department of Computer Science and Technology, Nanjing University, China. His research interests include RFID systems, software-defined radio, activity sensing, indoor localization, etc. WANG Chuyu is the corresponding author.|XIE Lei received his B.S. and Ph.D. degrees from Nanjing University, China in 2004 and 2010, respectively, all in computer science. He is a full professor in the Department of Computer Science and Technology, Nanjing University, China. He has published over 100 papers in IEEE Transactions on Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, ACM Transactions on Sensor Networks, ACM MOBICOM, ACM UbiComp, ACM MobiHoc, IEEE INFOCOM, IEEE ICNP, IEEE ICDCS, etc.
  • Supported by:
    National Natural Science Foundation of China(61902175);Natural Science Foundation of China(BK20190293)


Due to the function of gestures to convey information, gesture recognition plays a more and more important part in human-computer interaction. Traditional methods to recognize gestures are mostly device-based, which means users need to contact the devices. To overcome the inconvenience of the device-based methods, studies on device-free gesture recognition have been conducted. However, computer vision methods bring privacy issues and light interference problems. Therefore, we turn to wireless technology. In this paper, we propose a device-free in-air gesture recognition method based on radio frequency identification (RFID) tag array. By capturing the signals reflected by gestures, we can extract the gesture features. For dynamic gestures, both temporal and spatial features need to be considered. For static gestures, spatial feature is the key, for which a neural network is adopted to recognize the gestures. Experiments show that the accuracy of dynamic gesture recognition on the test set is 92.17%, while the accuracy of static ones is 91.67%.

Key words: gesture recognition, RFID tag array, neural network