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.

引用

页码：444 / 447

页数：4

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