Dynamic Hand Gesture Recognition Using FMCW Radar Sensor for Driving Assistance

Dynamic hand gesture recognition is very important for human-computer interaction. In vehicles, hand gesture recognition can be used as the driver’s auxiliary system to achieve remote control of the instrument. To a certain extent, this system can avoid physical buttons and touch screens causing interference to the driver. In this paper, we describe a driver assisted dynamic gesture recognition system to classify nine hand gestures based on micro-Doppler signatures obtained by 77GHz FMCW radar using a convolutional neural network (CNN). We further explore the changes in the accuracy of same gestures in a variety of experimental scenarios to help optimize the robustness of the system.

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