Visual Attention Model Based Visual Hierarchy Recommendation Framework for Improved User Experience Design Dataset

A dataset comprising videos recorded through the Gaze Cloud Eye Tracker, a sophisti- cated eye tracking system is used. Each video in the dataset includes two crucial visual components: a heatmap and a circle pointer, illustrating the user’s eye movement dur- ing the recording. Calibration is done before each video session to address any potential errors. The calibration process involves a thorough review of the user’s setup including the monitor dimensions, the distance at which the user is from the screen and the po- sition of his eyeballs and gaze. This calibration process emphasizes the precision and dependability of the captured eye movement data. Each video within the dataset cap- tures the user’s browsing activity on a website. This unintentional browsing scenario is intended to simulate a more natural and free-flowing user experience, allowing for a comprehensive analysis of eye movements in a real-world web browsing context.