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arXiv · 2509.10969

Gaze Authentication: Factors Influencing Authentication Performance

Dillon Lohr·Michael J Proulx·Mehedi Hasan Raju·Oleg V Komogortsev
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Abstract

This paper examines the key factors that influence the performance of state-of-the-art gaze-based authentication. Experiments were conducted on a large-scale, in-house dataset comprising 8,849 subjects collected with Meta Quest Pro equivalent hardware running a video oculography-driven gaze estimation pipeline at 72~Hz. State of the neural network architecture was employed to study the influence of the following factors on authentication performance: eye tracking signal quality, various aspects of eye tracking calibration, and simple filtering on estimated raw gaze. This report provides performance results and their analysis.

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Dillon Lohr, Michael J Proulx, Mehedi Hasan Raju, Oleg V Komogortsev. 2025-09-13. Gaze Authentication: Factors Influencing Authentication Performance. https://arxiv.org/abs/2509.10969

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