Human eye movements as a trait for biometrical identification

This research work proposes an innovative processing scheme for the exploitation of eye movement dynamics on the field of biometrical identification. As the mechanisms that derive eye movements highly depend on each person's idiosyncrasies, cues that reflect at a certain extent individual characteristics may be captured and subsequently deployed for the implementation of a robust identification system. Our methodology involves the employment of a non - parametric statistical test, the multivariate Wald - Wolfowitz test (WW-test), in order to compare the distributions of saccadic velocity and acceleration features, which are extracted while a person fixates on visual stimuli. In the evaluation section we use two publicly available datasets that supply recorded eye movements from a number of subjects during the observation of a moving spot on a computer screen. The resulting identification rates exhibit the efficacy of the suggested scheme to adequately segregate people according to their eye movement traits.