Biometric identification via an oculomotor plant mathematical model

There 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...

• Type: Conference
• Year: 2010
• Where: ETRA
• Authors: Oleg V. Komogortsev, Sampath Jayarathna, Cecilia R. Aragon, Mechehoul Mahmoud
• Keywords: Biometric Identification, ETRA 2010, Eye Movement, Eye Tracking Research, Oculomotor Plant