Problem
Research questions and friction points this paper is trying to address.
marker-free
eye-gaze estimation
single image
depth from defocus
Marker-free eye-gaze estimation using a single image and depth from defocus
🤖 AI Summary
本文提出了一种无需标记的单目眼动估计方法，通过深度脱焦估算头部姿态和虹膜位置，并使用变分贝叶斯多项逻辑回归映射视线。
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
marker-free eye-gaze estimation
depth from defocus
variational Bayesian multinomial logistic regression
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