English(EN) Marker-free eye-gaze estimation using a single image and depth from defocus

无标记眼动追踪使用单摄像头和离焦深度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

研究人员开发了一种新颖的无标记眼动追踪方法，该方法使用单个2D摄像头（如笔记本电脑摄像头）来估计眼动。该方法利用了从离焦深度技术获得的虹膜定位和头部姿态估计。一个变分贝叶斯多项逻辑回归框架将这些特征映射到用户的注视点，并在用户观看不同距离屏幕的实验中证明了其有效性。 AI

影响这种无标记眼动追踪可以增强人机交互和辅助功能工具。

排序理由该条目是一篇提交给arXiv的学术论文，详细介绍了一种新方法。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · David Hurtubise-Martin, Feriel Fass, Djemel Ziou, Marie-Flavie Auclair-Fortier · 2026-09-10 04:00

使用单张图像和离焦深度进行无标记眼动追踪

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…