Clustering-Driven DGS-Based Micro-Doppler Feature Extraction for Automatic Dynamic Hand Gesture Recognition

Clustering-Driven DGS-Based Micro-Doppler Feature Extraction for Automatic Dynamic Hand Gesture Recognition

We propose in this work a dynamic group sparsity (DGS) based time-frequency feature extraction method for dynamic hand gesture recognition (HGR) using millimeter-wave radar sensors. Micro-Doppler signatures of hand gestures show both sparse and structured characteristics in time-frequency domain, bu...

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Bibliographic Details
Main Authors: Chengjin Zhang, Zehao Wang, Qiang An, Shiyong Li, Ahmad Hoorfar, Chenxiao Kou
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
dynamic hand gesture recognition
sparse signal representation
dynamic group sparsity
micro-Doppler features
Online Access:https://www.mdpi.com/1424-8220/22/21/8535

Internet

https://www.mdpi.com/1424-8220/22/21/8535

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