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, 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.

Automated summary

This article introduces a large eye-tracking-based dataset UEyes and its analysis results. The authors compare and analyze the influences of factors such as color, location, and gaze direction on four major UI types: webpage, desktop UI, mobile UI, and poster. They also propose improvements for predictive models to better capture typical tendencies across UI types.