ETH-XGaze: A Large Scale Dataset for Gaze Estimation Under Extreme Head Pose and Gaze Variation


METADATA ONLY
Loading...

Date

2020

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

Gaze estimation is a fundamental task in many applications of computer vision, human computer interaction and robotics. Many state-of-the-art methods are trained and tested on custom datasets, making comparison across methods challenging. Furthermore, existing gaze estimation datasets have limited head pose and gaze variations, and the evaluations are conducted using different protocols and metrics. In this paper, we propose a new gaze estimation dataset called ETH-XGaze, consisting of over one million high-resolution images of varying gaze under extreme head poses. We collect this dataset from 110 participants with a custom hardware setup including 18 digital SLR cameras and adjustable illumination conditions, and a calibrated system to record ground truth gaze targets. We show that our dataset can significantly improve the robustness of gaze estimation methods across different head poses and gaze angles. Additionally, we define a standardized experimental protocol and evaluation metric on ETH-XGaze, to better unify gaze estimation research going forward. The dataset and benchmark website are available at https://ait.ethz.ch/projects/2020/ETH-XGaze.

Publication status

published

Book title

Computer Vision – ECCV 2020

Volume

12350

Pages / Article No.

365 - 381

Publisher

Springer

Event

16th European Conference on Computer Vision (ECCV 2020) (virtual)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03979 - Hilliges, Otmar (ehemalig) / Hilliges, Otmar (former) check_circle
09686 - Tang, Siyu / Tang, Siyu check_circle
00002 - ETH Zürich

Notes

Due to the Coronavirus (COVID-19) the conference was conducted virtually.

Funding

717054 - Optimization-based End-User Design of Interactive Technologies (EC)

Related publications and datasets