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

arXiv: https://arxiv.org/abs/2609.09610 · HTML: https://mlsanity.com/paper/2609.09610/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 60 references that are in the map.
- First posted on arXiv 9 Sep 2026.

## Builds on (most cited first, 15 of 15)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Gaze360: Physically Unconstrained Gaze Estimation in the Wild](https://mlsanity.com/paper/1910.10088/) (2019)
- [Eye Tracking for Everyone](https://mlsanity.com/paper/1606.05814/) (2016)
- [Appearance-Based Gaze Estimation in the Wild](https://mlsanity.com/paper/1504.02863/) (2015)
- [ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation](https://mlsanity.com/paper/2007.15837/) (2020)
- [MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation](https://mlsanity.com/paper/1711.09017/) (2017)
- [Appearance-based Gaze Estimation With Deep Learning: A Review and Benchmark](https://mlsanity.com/paper/2104.12668/) (2021)
- [Gaze Estimation using Transformer](https://mlsanity.com/paper/2105.14424/) (2021)
- [Towards End-to-end Video-based Eye-Tracking](https://mlsanity.com/paper/2007.13120/) (2020)
- [Evaluation of Appearance-Based Methods and Implications for Gaze-Based Applications](https://mlsanity.com/paper/1901.10906/) (2019)
- [A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms](https://mlsanity.com/paper/1708.01817/) (2017)
- [TabletGaze: Unconstrained Appearance-based Gaze Estimation in Mobile Tablets](https://mlsanity.com/paper/1508.01244/) (2015)
- [Accurate Eye Tracking from Dense 3D Surface Reconstructions using Single-Shot Deflectometry](https://mlsanity.com/paper/2308.07298/) (2023)
- [Real Time GAZED: Online Shot Selection and Editing of Virtual Cameras from Wide-Angle Monocular Video Recordings](https://mlsanity.com/paper/2311.15581/) (2023)
- [Prediction of rare events in the operation of household equipment using co-evolving time series](https://mlsanity.com/paper/2312.09410/) (2023)

## Abstract (arXiv)

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.