Biometric identification based on the eye movements and graph matching techniques
The last few years a growing research interest has aroused in the field of biometrics, concerning the use of brain dependent characteristics generally known as behavioral features. Human eyes, often referred as the gates to the soul, can possibly comprise a rich source of idiosyncratic information which may be used for the recognition of an individuals identity. In this paper an innovative experiment and a novel processing approach for the human eye movements is implemented, ultimately aiming at the biometric segregation of individual persons. In our experiment, the subjects observe face images while their eye movements are being monitored, providing information about each participants attention spots. The implemented method treats eye trajectories as 2-D distributions of points on the image plane. The efficiency of graph objects in the representation of structural information motivated us on the utilization of a non-parametric multivariate graph-based measure for the comparison of eye movement signals, yielding promising results at the task of identification according to behavioral characteristics of an individual.
eye movements behavioral biometrics face perception minimum spanning tree waldwolfowitz test