Browsing by Author "Hao, Qi"
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Item type:Item, A pyroelectric infrared biometric system for real-time walker recognition by use of a maximum likelihood principal components estimation (MLPCE) method(2007-03-19) ;Fang, Jian-Shuen ;Hao, Qi ;Brady, David J. ;Guenther, Bob D.Hsu, Ken Y.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. (c) 2007 Optical Society of America.Item type:Item, Real-time human identification using a pyroelectric infrared detector array and hidden Markov models(2006-07-24) ;Fang, Jian-Shuen ;Hao, Qi ;Brady, David J. ;Guenther, Bob D.Hsu, Ken Y.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. (c) 2006 Optical Society of America.