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Marker-free eye-gaze estimation using a single image and depth from defocus

2026-09-09 02:07:40
David Hurtubise-Martin, Feriel Fass, Djemel Ziou, Marie-Flavie Auclair-Fortier

Abstract

This paper presents a marker-free eye-gaze estimation approach using a single 2D camera, such as an integrated laptop webcam. The gaze-related features are estimated from iris localization and head pose estimated by using depth from defocus. A variational Bayesian multinomial logistic regression framework is used as mapping from the estimated features to the position of regard, based on an 8-dimensional feature vector of head-pose and iris-displacement parameters. No external marker is needed. Experiments were conducted by estimating the gaze of people watching a computer screen at different distances and compared against five existing methods. The obtained scores demonstrate the effectiveness of the proposed approach.

Abstract (translated)

URL

https://arxiv.org/abs/2609.09610

PDF

https://arxiv.org/pdf/2609.09610.pdf


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