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Fairness in Oculomotoric Biometric Identification

Prasse, Paul; Reich, David Robert; Makowski, Silvia; Jäger, Lena A; Scheffer, Tobias (2022). Fairness in Oculomotoric Biometric Identification. In: ETRA '22: 2022 Symposium on Eye Tracking Research and Applications, Seattle WA USA, 2022. ACM, 1-8.

Abstract

Gaze patterns are known to be highly individual, and therefore eye movements can serve as a biometric characteristic. We explore aspects of the fairness of biometric identification based on gaze patterns. We find that while oculomotoric identification does not favor any particular gender and does not significantly favor by age range, it is unfair with respect to ethnicity. Moreover, fairness concerning ethnicity cannot be achieved by balancing the training data for the best-performing model.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Scopus Subject Areas:Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Human-Computer Interaction
Health Sciences > Ophthalmology
Life Sciences > Sensory Systems
Language:English
Event End Date:2022
Deposited On:14 Feb 2023 16:06
Last Modified:29 Jun 2023 07:09
Publisher:ACM
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1145/3517031.3529633
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