Real-time human identification using a pyroelectric infrared detector array and hidden Markov models

Jian Shuen Fang, Qi Hao, David J. Brady, Bob D. Guenther, Ken Y. Hsu

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

Abstract

This paper proposes a real-time human identification system using a pyroelectric infrared (PIR) detector array and hidden Markov models (HMMs). A PIR detector array with masked Fresnel lens arrays is used to generate digital sequential data that can represent a human motion feature. HMMs are trained to statistically model the motion features of individuals through an expectation-maximization (EM) learning process. Human subjects are recognized by evaluating a set of new feature data against the trained HMMs using the maximum-likelihood (ML) criterion. We have developed a prototype system to verify the proposed method. Sensor modules with different numbers of detectors and different sampling masks were tested to maximize the identification capability of the sensor system.

Original languageEnglish (US)
Pages (from-to)6643-6658
Number of pages16
JournalOptics Express
Volume14
Issue number15
DOIs
StatePublished - 2006
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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