Title :
Human infrared signal recognition using single PIR detector
Author_Institution :
Chongqing Coll. of Electr. Eng., Chongqing, China
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;
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
DOI :
10.1109/CISP.2011.6100680
