Tracking and Recognition of Multiple Human Targets Moving in a Wireless Pyroelectric Infrared Sensor Network

Sensors

Ji Xiong²  Fangmin Li¹  Ning Zhao² 

[1] Key Laboratory of Fiber Optic Sensing Technology and Information Processing, School of Information and Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China;

关键词: multiple human identification;    distributed wireless pyroelectric sensor network;    empirical mode decomposition;    feature extracting;   

DOI  :  10.3390/s140407209

来源: mdpi

【 摘 要 】

With characteristics of low-cost and easy deployment, the distributed wireless pyroelectric infrared sensor network has attracted extensive interest, which aims to make it an alternate infrared video sensor in thermal biometric applications for tracking and identifying human targets. In these applications, effectively processing signals collected from sensors and extracting the features of different human targets has become crucial. This paper proposes the application of empirical mode decomposition and the Hilbert-Huang transform to extract features of moving human targets both in the time domain and the frequency domain. Moreover, the support vector machine is selected as the classifier. The experimental results demonstrate that by using this method the identification rates of multiple moving human targets are around 90%.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.