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

Jian-Shuen Fang | Zendy; Qi Hao | Zendy; David J. Brady | Zendy; B. D. Guenther | Zendy; Ken Y. Hsu | Zendy

Open Access

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

Author(s) -

Jian-Shuen Fang,

Qi Hao,

David J. Brady,

B. D. Guenther,

Ken Y. Hsu

Publication year - 2007

Publication title -

optics express

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.394

H-Index - 271

ISSN - 1094-4087

DOI - 10.1364/oe.15.003271

Subject(s) - biometrics , pattern recognition (psychology) , principal component analysis , artificial intelligence , computer science , signal (programming language) , signal processing , computer vision , support vector machine , digital signal processing , computer hardware , programming language

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.

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