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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Detalles Bibliográficos
Autores principales: Zhang, Chengjin, Wang, Zehao, An, Qiang, Li, Shiyong, Hoorfar, Ahmad, Kou, Chenxiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657879/
https://www.ncbi.nlm.nih.gov/pubmed/36366232
http://dx.doi.org/10.3390/s22218535

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657879/
https://www.ncbi.nlm.nih.gov/pubmed/36366232
http://dx.doi.org/10.3390/s22218535

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