Eye Tracking Visualization

Abstract

Eye tracking has become a widely used method to analyze user behavior in marketing, neuroscience, human-computer interaction, and visualization research. Apart from measuring completion times and recording accuracy rates of correctly given answers during the performance of visual tasks in classical controlled user experiments, eye tracking-based evaluations provide additional information on how visual attention is distributed and changing for a presented stimulus. Due to the wide field of applications of eye tracking and various kinds of research questions, different approaches have been developed to analyze eye tracking data such as statistical algorithms (either descriptive or inferential), string editing algorithms, visualization-related techniques, and visual analytics techniques. Regardless of whether statistical or visual methods are used for eye tracking data analysis, a large amount of data generated during eye tracking experiments has to be handled.