UEyes: An Eye-Tracking Dataset across User Interface Types

February 07, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Yue Jiang, Luis A. Leiva, Paul R. B. Houssel, Hamed R. Tavakoli, Julia KylmΓ€lΓ€, Antti Oulasvirta arXiv ID 2402.05202 Category cs.HC: Human-Computer Interaction Citations 6 Venue arXiv.org Last Checked 4 months ago
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.
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