Dynamic Hand Gesture Classification Based on Radar Micro-Doppler Signatures

被引：0

作者：

Zhang, Shimeng ^{[1
]}

Li, Gang ^{[1
]}

Ritchie, Matthew ^{[2
]}

Fioranelli, Francesco ^{[3
]}

Griffiths, Hugh ^{[2
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China

[2] UCL, Dept Elect & Elect Engn, London WC1E 7JE, England

[3] Univ Glasgow, Sch Elect Engn, Glasgow, Lanark, Scotland

来源：

2016 CIE INTERNATIONAL CONFERENCE ON RADAR (RADAR) | 2016年

基金：

中国国家自然科学基金;

关键词：

hand gesture classification; micro-Doppler signatures; support vector machine; human-computer interaction; RECOGNITION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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%.

引用

页数：4

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