A Dynamic Continuous Hand Gesture Detection and Recognition Method with FMCW Radar

Ren, Aihu; Wang, Yong; Yang, Xiaobo; Zhou, Mu

doi:10.1109/iccc49849.2020.9238935

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Zhou et al [44] obtained the total time of a single hand gesture and realized the detection of continuous gestures. Ren et al [45] obtained the amplitude by normalizing the hand gesture target and setting a threshold to effectively segment the continuous gestures.…”

Section: Gesturesmentioning

confidence: 99%

Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results

Tang,

Wu,

2023

Sensors

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As a convenient and natural way of human-computer interaction, gesture recognition technology has broad research and application prospects in many fields, such as intelligent perception and virtual reality. This paper summarized the relevant literature on gesture recognition using Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar from January 2015 to June 2023. In the manuscript, the widely used methods involved in data acquisition, data processing, and classification in gesture recognition were systematically investigated. This paper counts the information related to FMCW millimeter wave radar, gestures, data sets, and the methods and results in feature extraction and classification. Based on the statistical data, we provided analysis and recommendations for other researchers. Key issues in the studies of current gesture recognition, including feature fusion, classification algorithms, and generalization, were summarized and discussed. Finally, this paper discussed the incapability of the current gesture recognition technologies in complex practical scenes and their real-time performance for future development.

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Section: Gesturesmentioning

confidence: 99%

Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results

Tang,

Wu,

2023

Sensors

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“…A Template Matching Based Radar Gesture Recognition Algorithm. Dynamic time warping (DTW) [29][30][31] is currently the most common template matching algorithm for radar gesture recognition. A reference template set needs to be constructed first when using DTW to process radar data.…”

Section: Gesture Feature Extraction and Classification Recognition Al...mentioning

confidence: 99%

Human Gesture Recognition Based on Millimeter-Wave Radar Using Improved C3D Convolutional Neural Network

Li¹,

Li²,

Gao³

et al. 2023

Journal of Computers

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<p>In this paper, we propose a time sequential IC3D convolutional neural network approach for hand gesture recognition based on frequency modulated continuous wave (FMCW) radar. Firstly, the FMCW radar is used to collect the echoes of human hand gestures. A two-dimensional fast Fourier transform calculates the range and velocity information of hand gestures in each frame signal to construct the Range-Doppler heat map dataset of hand gestures. Then, we design an IC3D network for feature extraction and classification of the dynamic gesture heat map. Finally, the experiment results show that the gesture recognition system designed in this paper effectively solves the problems of the difficulty of human gesture feature extraction and low utilization of time series information, and the average recognition accuracy rate can reach more than 99.8%.</p> <p> </p>

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Real-Time Multi-target Activity Recognition Based on FMCW Radar

Pan

Liu

Shen

et al. 2021

Intelligent Equipment, Robots, and Vehicles

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A Dynamic Continuous Hand Gesture Detection and Recognition Method with FMCW Radar

Cited by 4 publications

References 16 publications

Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results

Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results

Human Gesture Recognition Based on Millimeter-Wave Radar Using Improved C3D Convolutional Neural Network

Real-Time Multi-target Activity Recognition Based on FMCW Radar

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