UEyes: Understanding Visual Saliency across User Interface Types


While user interfaces (UIs) display elements such as images and text in a grid-based layout, UI types differ significantly in the number of elements and how they are displayed. For example, webpage designs rely heavily on images and text, whereas desktop UIs tend to feature numerous small images. To examine how such differences affect the way users look at UIs, we collected and analyzed a large eye-tracking-based dataset, \textit{UEyes} (62 participants and 1,980 UI screenshots), covering four major UI types: webpage, desktop UI, mobile UI, and poster. We analyze its differences in biases related to such factors as color, location, and gaze direction. We also compare state-of-the-art predictive models and propose improvements for better capturing typical tendencies across UI types. Both the dataset and the models are publicly available.

Yue Jiang
Aalto University, Espoo, Finland
Luis A.. Leiva
University of Luxembourg, Esch-sur-Alzette, Luxembourg
Hamed Rezazadegan Tavakoli
Nokia Technologies, Espoo, Finland
Paul R. B. Houssel
University of Luxembourg, Esch-sur-Alzette, Luxembourg
Julia Kylmälä
Aalto University, Espoo, Finland
Antti Oulasvirta
Aalto University, Helsinki, Finland



会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: GUIs, Gaze, and Gesture-based Interaction

Hall C
6 件の発表
2023-04-25 18:00:00
2023-04-25 19:30:00