access icon free Biometric verification with eye movements: results from a long-term recording series

The authors present the author's results of using saccadic eye movements for biometric user verification. The method can be applied to computers or other devices, in which it is possible to include an eye movement camera system. Thus far, this idea has been little researched. As they have extensively studied eye movement signals for medical applications, they saw an opportunity for the biometric use of saccades. Saccades are the fastest of all eye movements, and are easy to stimulate and detect from signals. As signals measured from a physiological origin, the properties of eye movements (e.g. latency and maximum angular velocity) may contain considerable variability between different times of day, between days or weeks and so on. Since such variability might impair biometric verification based on saccades, they attempted to tackle this issue. In contrast to their earlier results, where they did not include such long intervals between sessions of eye movement recordings as in the present research, their results showed that – notwithstanding some variability present in saccadic variables – this variability was not considerable enough to essentially disturb or impair verification results. The only exception was a test series of very long intervals ∼16 or 32 months in length. For the best results obtained with various classification methods, false rejection and false acceptance rates were <5%. Thus, they conclude that saccadic eye movements can provide a realistic basis for biometric user verification.

Inspec keywords: cameras; iris recognition; gaze tracking; signal detection

Other keywords: false acceptance rates; signal detection; eye movement camera system; medical applications; maximum angular velocity; saccadic eye movements; false rejection rates; physiological origin; eye movement signals; biometric user verification; long-term recording series; eye movement recordings

Subjects: Image recognition; Image sensors; Computer vision and image processing techniques

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