Real-Time Radar-Based Gesture Detection and Recognition Built in an Edge-Computing Platform
IEEE Sensors Journal, vol. 20, pp. 10706–10716
Abstract
In this paper, a real-time signal processing framework based on a 60 GHz frequency-modulated continuous wave (FMCW) radar system to recognize gestures is proposed. In order to improve the robustness of the radar-based gesture recognition system, the proposed framework extracts a comprehensive hand profile, including range, Doppler, azimuth and elevation, over multiple measurement-cycles and encodes them into a feature cube. Rather than feeding the range-Doppler spectrum sequence into a deep convolutional neural network (CNN) connected with recurrent neural networks, the proposed framework takes the aforementioned feature cube as input of a shallow CNN for gesture recognition to reduce the computational complexity. In addition, we develop a hand activity detection (HAD) algorithm to automatize the detection of gestures in real-time case. The proposed HAD can capture the time-stamp at which a gesture finishes and feeds the hand profile of all the relevant measurement-cycles before this time-stamp into the CNN with low latency. Since the proposed framework is able to detect and classify gestures at limited computational cost, it could be deployed in an edge-computing platform for real-time applications, whose performance is notedly inferior to a state-of-the-art personal computer. The experimental results show that the proposed framework has the capability of classifying 12 gestures in real-time with a high${F}_{\sf 1}$-score.
Authors 6
-
Hella (Germany) · Ruhr University Bochum
Affiliation as printed
HELLA GmbH & Co. KGaA, Lippstadt, Germany
Institute for Integrated Systems, Ruhr-University Bochum, Bochum, Germany
HELLA GmbH & Co. KGaA, Lippstadt, Germany; Institute for Integrated Systems, Ruhr-University Bochum, Bochum, Germany
-
Affiliation as printed
HELLA GmbH & Co. KGaA, Lippstadt, Germany
-
Xibo Li Aachen
Affiliation as printed
RWTH Aachen University, Aachen, Germany
-
Affiliation as printed
HELLA GmbH & Co. KGaA, Lippstadt, Germany
-
Affiliation as printed
HELLA GmbH & Co. KGaA, Lippstadt, Germany
-
Affiliation as printed
Institute for Integrated Systems, Ruhr-University Bochum, Bochum, Germany
Cited by 143 stored of 145
Cited by patents worldwide 4 (Lens.org)
-
Method for transmitting and receiving radar signal and electronic device thereforUS12510646B2 2025-12-30 Active
-
METHODS AND APPARATUSES FOR LATENCY REDUCTION IN GESTURE RECOGNITION USING MMWAVE RADARUS20240053463A1 2024-02-15 Pending
-
RADAR-BASED GESTURE CLASSIFICATION USING A VARIATIONAL AUTO-ENCODER NEURAL NETWORK ALGORITHMEP4134924A1 2023-02-15 Active
-
Gesture recognition method based on MIMO millimeter-wave radarCN111650582A 2020-09-11 Active