Human infrared signal recognition using single PIR detector

Author

Wang, Linhong

Author_Institution

Chongqing Coll. of Electr. Eng., Chongqing, China

Volume

5

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

2664

Lastpage

2668

Abstract

A human recognition approach based on pyroelectric infrared (PIR) signal is proposed. The wavelet packet entropy (WPE) is employed for extracting the features of PIR signals, and then the least square support vector machine (LS-SVM) classifier is used as classifier. Relying on this approach, robust human recognition can be achieved with single PIR detector. The experiments show that the recognition rate is 91.2%, 1.3% higher than that of the traditional approach, meanwhile, the false alarm rate is reduced more than 4.0%.

Keywords

least squares approximations; pattern classification; pyroelectric detectors; signal processing; support vector machines; wavelet transforms; LS-SVM; feature extraction; human infrared signal recognition; least square support vector machine classifier; pyroelectric infrared signal; robust human recognition; single PIR detector; wavelet packet entropy; Detectors; Entropy; Feature extraction; Humans; Kernel; Wavelet packets; pattern recognition; pyroelectric sensor; signal processing; wavelet packet entropy;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2011 4th International Congress on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9304-3

Type

conf

DOI

10.1109/CISP.2011.6100680

Filename

6100680