Micro Gesture Recognition with Terahertz Radar Based on Diagonal Profile of Range-Doppler Map
Xing Wang, Rui Min, Zongyong Cui, Zongjie Cao · 2020
Gestures can be gradually used to achieve natural and direct communication between people and machines, not limited to people. However, micro gesture motion sensing using traditional sensors and techniques is challenging because of the difference and diversity of finger motion. This paper proposes a novel method for micro gesture recognition based on the high resolution of terahertz radar, which can capture fine changes during gesture movement. From these radar echoes collected in gesture motion, the low dimensional projection features of diagonal profile based on range-Doppler map (RDM) are extracted to characterize the motion difference between gestures. Then, a convolutional neural network (CNN) is employed to realize the gesture recognition system. The experimental results show that the proposed method can achieve a high recognition rate of 98.06% with six dynamic micro gestures across eight participants.