Yang, L., Li, G., Ritchie, M., Fioranelli, F. and Griffiths, H. (2017) Gait Classification Based on Micro-Doppler Features. In: 2016 CIE International Conference on Radar (Radar 2016), Guangzhou, China, 10-13 Oct 2016, (doi: 10.1109/RADAR.2016.8059301)
|
Text
150351.pdf - Accepted Version 572kB |
Publisher's URL: http://ieeexplore.ieee.org/document/8059301/
Abstract
This paper focuses on the classification of human gaits based on micro-Doppler signatures. The micro-Doppler signatures can represent detailed information about the human gaits, which helps in judging the threat of a personnel target. The proposed method consists of three major steps. Firstly, the micro-Doppler signatures are obtained by performing time-frequency analysis on the radar data. Then two micro-Doppler features are extracted from the time-frequency domain. Finally, the one-versus-one support vector machine (SVM) is used to realize multi-class classification. Experiments on real data show that, with the selected features, high classification accuracy of the human gaits of interest can be achieved.
Item Type: | Conference Proceedings |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Fioranelli, Dr Francesco and Ritchie, Mr Matthew |
Authors: | Yang, L., Li, G., Ritchie, M., Fioranelli, F., and Griffiths, H. |
College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
Copyright Holders: | Copyright © 2017 IEEE |
Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher. |
University Staff: Request a correction | Enlighten Editors: Update this record