Eye Know You: Metric Learning for End-to-end Biometric Authentication Using Eye Movements from a Longitudinal Dataset

dc.contributor.authorLohr, Dillon J.
dc.contributor.authorGriffith, Henry
dc.contributor.authorKomogortsev, Oleg
dc.date.accessioned2022-05-06T17:00:04Z
dc.date.available2022-05-06T17:00:04Z
dc.date.issued2022-04
dc.description.abstractThe permanence of eye movements as a biometric modality remains largely unexplored in the literature. The present study addresses this limitation by evaluating a novel exponentially-dilated convolutional neural network for eye move- ment authentication using a recently proposed longitudinal dataset known as GazeBase. The network is trained using multi-similarity loss, which directly enables the enrollment and authentication of out-of-sample users. In addition, this study includes an exhaustive analysis of the effects of evaluating on various tasks and downsampling from 1000 Hz to several lower sampling rates. Our results reveal that reasonable authentication accuracy may be achieved even during both a low-cognitive- load task and at low sampling rates. Moreover, we find that eye movements are quite resilient against template aging after as long as 3 years.
dc.description.departmentComputer Science
dc.description.versionThis is the author accepted manuscript version of an article published in IEEE Transactions on Biometrics, Behavior, and Identity Science.
dc.formatText
dc.format.extent13 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationLohr, D., Griffith, H., & Komogortsev, O. V. (2022). Eye know you: Metric learning for end-to-end biometric authentication using eye movements from a longitudinal dataset. IEEE Transactions on Biometrics, Behavior, and Identity Science, pp. 1-13.
dc.identifier.doihttps://doi.org/10.1109/TBIOM.2022.3167633
dc.identifier.issn2637-6407
dc.identifier.urihttps://hdl.handle.net/10877/15742
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.sourceIEEE Transactions on Bibliometrics, Behavior, and Identity Science, pp. 1-13.
dc.subjectbiometric authentication
dc.subjectmetric learning
dc.subjecttemplate aging
dc.subjectdilated convolution
dc.subjecteye movements
dc.subjectComputer Science
dc.titleEye Know You: Metric Learning for End-to-end Biometric Authentication Using Eye Movements from a Longitudinal Dataset
dc.typeArticle

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