UEyes: An Eye-Tracking Dataset across User Interface Types

TL;DR

This paper introduces UEyes, a comprehensive eye-tracking dataset across various user interface types, enabling analysis of visual attention differences influenced by UI design and layout.

Contribution

It provides a large, diverse eye-tracking dataset across four UI types, facilitating comparative analysis and future research in UI design and user attention.

Findings

Differences in gaze patterns across UI types

Impact of color and layout on visual attention

Variability in individual viewing strategies

Abstract

Different types of user interfaces differ significantly in the number of elements and how they are displayed. To examine how such differences affect the way users look at UIs, we collected and analyzed a large eye-tracking-based dataset, UEyes (62 participants, 1,980 UI screenshots, near 20K eye movement sequences), covering four major UI types: webpage, desktop UI, mobile UI, and poster. Furthermore, we analyze and discuss the differences in important factors, such as color, location, and gaze direction across UI types, individual viewing strategies and potential future directions. This position paper is a derivative of our recent paper with a particular focus on the UEyes dataset.