2D CNN-GRU Model for Multi-Hand Gesture Recognition System Using FMCW Radar
2022 20TH IEEE INTERREGIONAL NEWCAS CONFERENCE (NEWCAS)(2022)
摘要
Contactless human hand gesture recognition has received significant attention in the preceding decade. This paper proposes a novel classification approach utilizing an advanced 77-GHz multiple-input-multiple-output (MIMO) frequency modulated continuous wave (FMCW) radar. The pre-processed range-Doppler images (RDIs) and range-angle images (RAIs) of this radar are fed into a dual-stream artificial neural network comprised of 2D convolutional neural network-gated recurrent units (2D CNN-GRU) for human hand gesture classification. According to the conducted experiments, the average accuracy of the proposed classification model with 8-fold cross-validation achieves 92.50%.
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关键词
hand gesture recognition,MIMO radar,FMCW,machine learning,artificial neural networks
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