Gait-Based Person And Gender Recognition Using Micro-Doppler Signatures

被引：0
|
作者：
Garreau, Guillaume [1 ]
Andreou, Charalambos M. [1 ]
Andreou, Andreas G. [1 ]
Georgiou, Julius [1 ]
Dura-Bernal, Salvador [2 ]
Wennekers, Thomas [2 ]
Denham, Sue [2 ]
机构：
[1] Univ Cyprus, Holist Elect Res Lab, Kallipoleos 75, CY-1678 Nicosia, Cyprus
[2] Univ Plymouth, Ctr Robot & Neural Syst, Plymouth PL4 8AA, Devon, England
来源：
2011 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS) | 2011年
关键词：
Micro-Doppler; ultrasonic device; spectrogram; k-NN classifier; individual recognition; gender classification; RADAR;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The ability to identify an individual quickly and accurately is a critical parameter in surveillance. Conventional contactless systems are often complex and expensive to implement since video-based processing requires high computational resources. In this paper we present a micro-Doppler (mD) system and a computationally efficient classifier for the purpose of identifying individuals and gender. Walking subjects are successfully classified based on their mD time-frequency signatures. Recognition accuracies as high as 100% are obtained for some individuals and 92% for gender classification.
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页码：444 / 447
页数：4
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