UEyes: An Eye-Tracking Dataset across User Interface Types

Autor:	Jiang, Yue, Leiva, Luis A., Houssel, Paul R. B., Tavakoli, Hamed R., Kylmälä, Julia, Oulasvirta, Antti
Rok vydání:	2024
Předmět:	Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted as a CHI2023 workshop paper
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.05202 Zobrazit plný text záznamu View this record from Arxiv