Static hand gesture recognition based on 2-D SAR imaging

Cuicui Yang; Zhihai Zhuo; Xingshuai Qiao; Tao Shan

doi:10.1117/12.2607622

15 February 2022 Static hand gesture recognition based on 2-D SAR imaging

Cuicui Yang, Zhihai Zhuo, Xingshuai Qiao, Tao Shan

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121660V (2022) https://doi.org/10.1117/12.2607622
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

Hand gesture recognition has long been a study topic in the field of Human Computer Interaction. Compared with traditional camera-based recognition systems, radar can realize dynamic hand gesture recognition at long distances and in low light conditions by exploiting the micro-Doppler (m-D) effect. However, for some static and complex hand gestures, the m-D-based recognition methods are rendered impotent. In this paper, we present a method based on 2-D synthetic aperture radar (SAR) imaging to distinguish nine kinds of static hand gestures representing the numbers 1-9. A cost-effective 77 GHz mm-wave radar is used to achieve imaging and data acquisition of different gestures. Finally, two classifiers including classic machine learning and deep learning are used to evaluate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method can guarantee a promising recognition accuracy.

Citation Download Citation

Cuicui Yang, Zhihai Zhuo, Xingshuai Qiao, and Tao Shan "Static hand gesture recognition based on 2-D SAR imaging", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121660V (15 February 2022); https://doi.org/10.1117/12.2607622

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