Biometric Identification via an Oculomotor Plant Mathematical Model

dc.contributor.authorKomogortsev, Oleg
dc.contributor.authorJayarathna, Sampath
dc.contributor.authorAragon, Cecilia R.
dc.contributor.authorMahmoud, Mechehoul
dc.date.accessioned2009-11-24T10:03:29Z
dc.date.available2012-02-24T10:03:34Z
dc.date.issued2009-11-19
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.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent10 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationKomogortsev, O. V., Jayarathna, S., Aragon, C. R., & Mahmoud, M. (2009). Biometric identification via an oculomotor plant mathematical model (Report No. TXSTATE-CS-TR-2009-17). Texas State University-San Marcos, Department of Computer Science.
dc.identifier.urihttps://hdl.handle.net/10877/2587
dc.language.isoen
dc.subjectbiometrics
dc.subjectoculomotor plant
dc.subjecteye tracking
dc.subjectComputer Science
dc.titleBiometric Identification via an Oculomotor Plant Mathematical Model
dc.typeTechnical Report

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