Li, G., Zhang, S., Fioranelli, F. and Griffiths, H. (2018) Effect of sparsity-aware time–frequency analysis on dynamic hand gesture classification with radar micro-Doppler signatures. IET Radar, Sonar and Navigation, 12(8), pp. 815-820. (doi: 10.1049/iet-rsn.2017.0570)
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160032.pdf - Accepted Version 984kB |
Abstract
Dynamic hand gesture recognition is of great importance in human-computer interaction. In this study, the authors investigate the effect of sparsity-driven time-frequency analysis on hand gesture classification. The time-frequency spectrogram is first obtained by sparsity-driven time-frequency analysis. Then three empirical micro-Doppler features are extracted from the time-frequency spectrogram and a support vector machine is used to classify six kinds of dynamic hand gestures. The experimental results on measured data demonstrate that, compared to traditional time-frequency analysis techniques, sparsity-driven time-frequency analysis provides improved accuracy and robustness in dynamic hand gesture classification.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Fioranelli, Dr Francesco |
| Authors: | Li, G., Zhang, S., Fioranelli, F., and Griffiths, H. |
| College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | IET Radar, Sonar and Navigation |
| Publisher: | Institution of Engineering and Technology |
| ISSN: | 1751-8784 |
| ISSN (Online): | 1751-8792 |
| Published Online: | 27 April 2018 |
| Copyright Holders: | Copyright © 2018 The Institution of Engineering and Technology |
| First Published: | First published in IET Radar, Sonar and Navigation 12(8):815-820 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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