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Marker-free eye-gaze estimation uses single camera and depth from defocus

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel marker-free method for estimating eye gaze using a single 2D camera, such as a laptop webcam. This approach leverages iris localization and head pose estimation derived from depth-from-defocus techniques. A variational Bayesian multinomial logistic regression framework maps these features to the user's point of regard, demonstrating effectiveness in experiments with users watching screens at varying distances. AI

IMPACT This marker-free eye-gaze estimation could enhance human-computer interaction and accessibility tools.

RANK_REASON The item is an academic paper submitted to arXiv detailing a new methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Marker-free eye-gaze estimation uses single camera and depth from defocus

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The item is an academic paper submitted to arXiv detailing a new methodology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · David Hurtubise-Martin, Feriel Fass, Djemel Ziou, Marie-Flavie Auclair-Fortier ·

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

    arXiv:2609.09610v1 Announce Type: new 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…

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