Visualizing eye tracking data can provide insights in many research fields. However, visualizing such data efficiently and cost-effectively is challenging without well-designed tools. Easily accessible web-based approaches equipped with intuitive and interactive visualizations offer to be a promising solution. Many of such tools already exist, however, they mostly use one specific visualization technique. In this paper, we describe a web application which uses a combination of different visualization methods for eye tracking data. The visualization techniques are interactively linked to provide several perspectives on the eye tracking data. We conclude the paper by discussing challenges, limitations, and future work.
|Title of host publication||Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings|
|Editors||Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani|
|Publisher||Springer Science and Business Media B.V.|
|Number of pages||15|
|Publication status||Published - 2021|
|Event||25th International Conference on Pattern Recognition Workshops, ICPR 2020 - Milan, Italy|
Duration: 10 Jan 2021 → 11 Jan 2021
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||25th International Conference on Pattern Recognition Workshops, ICPR 2020|
|Period||10/01/21 → 11/01/21|
Bibliographical notePublisher Copyright:
© 2021, Springer Nature Switzerland AG.
Copyright 2021 Elsevier B.V., All rights reserved.
- Eye tracking
- Information visualization
- Multiple linked views