A pyroelectric infrared biometric system for real-time walker recognition by use of a maximum likelihood principal components estimation (MLPCE) method

Jian Shuen Fang*, Qi Hao, David J. Brady, Bob D. Guenther, Ken-Yuh Hsu

*Corresponding author for this work

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

This paper presents a novel biometric system for real-time walker recognition using a pyroelectric infrared sensor, a Fresnel lens array and signal processing based on the linear regression of sensor signal spectra. In the model training stage, the maximum likelihood principal components estimation (MLPCE) method is utilized to obtain the regression vector for each registered human subject. Receiver operating characteristic (ROC) curves are also investigated to select a suitable threshold for maximizing subject recognition rate. The experimental results demonstrate the effectiveness of the proposed pyroelectric sensor system in recognizing registered subjects and rejecting unknown subjects.

Original languageEnglish
Pages (from-to)3271-3284
Number of pages14
JournalOptics Express
Volume15
Issue number6
DOIs
StatePublished - 19 Mar 2007

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