Michael Burch, Alberto Veneri, and Bangjie Sun. 2019. EyeClouds: A Visualization and Analysis Tool for Exploring Eye Movement Data. In Proceedings of the 12th International Symposium on Visual Information Communication and Interaction (VINCI’2019). Association for Computing Machinery, New York, NY, USA, Article 8, 1–8. [paper]

Abstract

In this paper, we discuss and evaluate the advantages and disadvantages of several techniques to visualize and analyze eye movement data tracked and recorded from public transport map viewers in a formerly conducted eye tracking experiment. Such techniques include heat maps and gaze stripes. To overcome the disadvantages and improve the effectiveness of those techniques, we present a viable solution that makes use of existing techniques such as heat maps and gaze stripes, as well as attention clouds which are inspired by the general concept of word clouds. We also develop a web application with interactive attention clouds, named the EyeCloud, to put theory into practice. The main objective of this paper is to help public transport map designers and producers gain feedback and insights on how the current design of the map can be further improved, by leveraging on the visualization tool. In addition, this visualization tool, the EyeCloud, can be easily extended to many other purposes with various types of data. It could be possibly applied to entertainment industries, for instance, to track the attention of the film audiences in order to improve the advertisements.