GazeVis : An Eye-Tracking Visualization Towards Predicting User Distraction CPSC 547 Project Report

We introduce GazeVis, a tool to visualize data gathered from a PDF reader application called GazeReader developed in another course. Our visualization aims to understand a reader’s gaze pattern before a self interruption occurs. We achieve this by allowing users to interactively inspect gaze related features over time. Furthermore, our visualization incorporates a prediction that determines if an amount of time is classified as normal reading or a reading before an interruption. In order to improve this prediction result our visualization supports the users while inspecting and cleaning the data. By integrating data cleansing with our prediction results, we enable our users to come up with a comprehensible way of understanding self interruption from gaze related features.