Dynamic Hand Gesture Classification Based on Radar Micro-Doppler Signatures

Zhang, S., Li, G., Ritchie, M., Fioranelli, F. and Griffiths, H. (2017) Dynamic Hand Gesture Classification Based on Radar Micro-Doppler Signatures. In: 2016 CIE International Conference on Radar (Radar 2016), Guangzhou, China, 10-13 Oct 2016, (doi:10.1109/RADAR.2016.8059518)

[img]
Preview
Text
150350.pdf - Accepted Version

623kB

Abstract

Dynamic hand gesture recognition is of great importance for human-computer interaction. In this paper, we present a method to discriminate the four kinds of dynamic hand gestures, snapping fingers, flipping fingers, hand rotation and calling, using a radar micro-Doppler sensor. Two micro-Doppler features are extracted from the time-frequency spectrum and the support vector machine is used to classify these four kinds of gestures. The experimental results on measured data demonstrate that the proposed method can produce a classification accuracy higher than 88.56%.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Fioranelli, Dr Francesco and Ritchie, Mr Matthew
Authors: Zhang, S., 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