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dc.contributor.authorKomogortsev, Oleg V.en_US
dc.contributor.authorJayarathna, Sampathen_US
dc.contributor.authorAragon, Cecilia R.en_US
dc.contributor.authorMahmoud, Mechehoulen_US
dc.date.accessioned2009-11-24en_US
dc.date.available2012-02-24T10:03:34Z
dc.date.issued2009-11-19en_US
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/2587
dc.descriptionReport Number TXSTATE-CS-TR-2009-17.en_US
dc.description.abstractThere has been increased interest in reliable, non-intrusive methods of biometric identification due to the growing emphasis on security and increasing prevalence of identity theft. This paper presents a new biometric approach that involves an estimation of the unique oculomotor plant (OP) or eye globe muscle parameters from an eye movement trace. These parameters model individual properties of the human eye, including neuronal control signal, series elasticity, length tension, force velocity, and active tension. These properties can be estimated for each extraocular muscle, and have been shown to differ between individuals. We describe the algorithms used in our approach and the results of an experiment with 41 human subjects tracking a jumping dot on a screen. Our results show improvement over existing eye movement biometric identification methods. The technique of using Oculomotor Plant Mathematical Model (OPMM) parameters to model the individual eye provides a number of advantages for biometric identification: it includes both behavioral and physiological human attributes, is difficult to counterfeit, non- intrusive, and could easily be incorporated into existing biometric systems to provide an extra layer of security.en_US
dc.formatText
dc.format.extent10 pages
dc.format.medium1 file (.pdf)
dc.language.isoen_US
dc.subjectBiometricsen_US
dc.subjectOculomotor planten_US
dc.subjectEye trackingen_US
dc.subject.classificationArtificial Intelligence and Roboticsen_US
dc.subject.classificationComputer Sciencesen_US
dc.titleBiometric Identification via an Oculomotor Plant Mathematical Modelen_US
txstate.publication.titleTechnical Reports-Computer Scienceen_US
txstate.documenttypeTechnical Report


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