UEyes: An Eye-Tracking Dataset across User Interface Types

Fuente: arXiv
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Hauptverfasser: Jiang, Yue, Leiva, Luis A., Houssel, Paul R. B., Tavakoli, Hamed R., Kylmälä, Julia, Oulasvirta, Antti
Format: Preprint
Veröffentlicht: 2024
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author Jiang, Yue
Leiva, Luis A.
Houssel, Paul R. B.
Tavakoli, Hamed R.
Kylmälä, Julia
Oulasvirta, Antti
author_facet Jiang, Yue
Leiva, Luis A.
Houssel, Paul R. B.
Tavakoli, Hamed R.
Kylmälä, Julia
Oulasvirta, Antti
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2402_05202
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle UEyes: An Eye-Tracking Dataset across User Interface Types
Jiang, Yue
Leiva, Luis A.
Houssel, Paul R. B.
Tavakoli, Hamed R.
Kylmälä, Julia
Oulasvirta, Antti
Human-Computer Interaction
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.
title UEyes: An Eye-Tracking Dataset across User Interface Types
topic Human-Computer Interaction
url https://arxiv.org/abs/2402.05202