English

UEyes: An Eye-Tracking Dataset across User Interface Types

Human-Computer Interaction 2024-02-09 v1

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.

Keywords

Cite

@article{arxiv.2402.05202,
  title  = {UEyes: An Eye-Tracking Dataset across User Interface Types},
  author = {Yue Jiang and Luis A. Leiva and Paul R. B. Houssel and Hamed R. Tavakoli and Julia Kylmälä and Antti Oulasvirta},
  journal= {arXiv preprint arXiv:2402.05202},
  year   = {2024}
}

Comments

Accepted as a CHI2023 workshop paper

R2 v1 2026-06-28T14:42:10.272Z