|dc.description.abstract||Eye movements present a novel and unique solution to the challenges faced by modern biometrics. Consisting of both physical and neurological components, and due to the minute scale, the accurate replication of eye movements outside of a living subject is practically infeasible (if not impossible), providing an inherent level of liveness detection and counterfeit-resistance. Further, recent advances in video-oculography allow for the efficient capture of eye movements from even low-quality image sensors, reducing the cost of entry and enabling integration with many existing iris, periocular, and facial recognition systems.
The following thesis describes the development of biometric techniques for the automated identification of human subjects based on patterns of eye movements that occur naturally during directed viewing of a visual stimulus. The proposed techniques are then evaluated according to standard practices in the biometric field to assess performance under varying environmental conditions. The results of this evaluation are analyzed to provide recommendations for suitable applications of the described techniques and direction for future research in this area.||