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arXiv · 2002.02591

Long-Range Gesture Recognition Using Millimeter Wave Radar

Yu Liu·Yuheng Wang·Haipeng Liu·Anfu Zhou·Jianhua Liu·Ning Yang
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Abstract

Millimeter wave (mmWave) based gesture recognition technology provides a good human computer interaction (HCI) experience. Prior works focus on the close-range gesture recognition, but fall short in range extension, i.e., they are unable to recognize gestures more than one meter away from considerable noise motions. In this paper, we design a long-range gesture recognition model which utilizes a novel data processing method and a customized artificial Convolutional Neural Network (CNN). Firstly, we break down gestures into multiple reflection points and extract their spatial-temporal features which depict gesture details. Secondly, we design a CNN to learn changing patterns of extracted features respectively and output the recognition result. We thoroughly evaluate our proposed system by implementing on a commodity mmWave radar. Besides, we also provide more extensive assessments to demonstrate that the proposed system is practical in several real-world scenarios.

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Yu Liu, Yuheng Wang, Haipeng Liu, Anfu Zhou, Jianhua Liu, Ning Yang. 2020-02-07. Long-Range Gesture Recognition Using Millimeter Wave Radar. https://arxiv.org/abs/2002.02591

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