NDLI: Biometric verification with eye movements: results from a long-term recording series

Content Provider	IET Digital Library
Author	Zhang, Youming Laurikkala, Jorma Juhola, Martti
Abstract	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.
Starting Page	162
Ending Page	168
Page Count	7
ISSN	20474938
Volume Number	4
e-ISSN	20474946
Issue Number	Issue 3, Sep (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/4/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2014.0044
Journal	IET Biometrics
Publisher Date	2015-02-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biometric User Verification Camera Computer Vision And Image Processing Technique Eye Movement Camera System Eye Movement Recordings Eye Movement Signal False Acceptance Rates False Rejection Rates Gaze Tracking Image Recognition Image Sonsor Iris Recognition Long-term Recording Series Maximum Angular Velocity Medical Application Physiological Origin Saccadic Eye Movement Signal Detection
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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