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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Fang, J-S; Hao, Q; Brady, DJ; Guenther, BD; Hsu, KY

Published Date

  • March 2007

Published In

Volume / Issue

  • 15 / 6

Start / End Page

  • 3271 - 3284

PubMed ID

  • 19532568

Pubmed Central ID

  • 19532568

Electronic International Standard Serial Number (EISSN)

  • 1094-4087

International Standard Serial Number (ISSN)

  • 1094-4087

Digital Object Identifier (DOI)

  • 10.1364/oe.15.003271

Language

  • eng