WU Jiaying, WANG Chuyu, XIE Lei
(State Key Laboratory for Novel Software Technology, Nanjing 210023, China)
Abstract: 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. Experiment show that the accuracy of dynamic gesture recognition on the test set is 92.17%, while the accuracy of static ones is 91.67%.
Keywords: gesture recognition; RFID tag array; neural network