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 Y. Hsu

Research output: Contribution to journalArticlepeer-review

35 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 (US)
Pages (from-to)3271-3284
Number of pages14
JournalOptics Express
Volume15
Issue number6
DOIs
StatePublished - Mar 19 2007
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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