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)

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.