Change search
ReferencesLink to record
Permanent link

Direct link
Comparison of Two Eye Trackers for the Visualization of Eye Tracking Data in Node-Link Diagrams
Linnaeus University, Faculty of Technology, Department of Computer Science.
Linnaeus University, Faculty of Technology, Department of Computer Science.
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The usage of eye trackers is becoming more and more popular in the field of information visualization. In this project two eye trackers, The Eye Tribe nd Mirametrix S2, are used to obtain eye tracking data for visualizations. It is planned to use the eye trackers with OnGraX, a network visualization system, where they will provide data for the implementation of visualizations, specifically, heatmaps. OnGraX already uses heatmaps to show regions in a network that have been in the viewport of the user. One aim of this thesis will be the comparison between the two eye trackers, and if the use of eye tracking data gives better results thatn the already existing viewport-based approach. At the same time, we provide the foundation for adaptive visualizations with OnGraX. Our research problem is also of interest for visualization in general, because it will help to improve and develop eye tracking technology in this context. To support the outcome of our implementation, we carried out a user study. As a result, we concluded that one of the two eye trackers appears to have more capabilities than the other, and that using the eye tracking data is a more preferred way of depicting the heatmaps on OnGraX.    

Place, publisher, year, edition, pages
2016. , 52 p.
Keyword [en]
Eye Tracking, Eye Trackers, Visualization, Heatmaps, OnGraX, The Eye Tribe, Mirametrix S2
National Category
Computer Science
URN: urn:nbn:se:lnu:diva-55733OAI: diva2:955553
Subject / course
Computer Science
Educational program
Software Technology Programme, 180 credits
Available from: 2016-08-29 Created: 2016-08-24 Last updated: 2016-08-29Bibliographically approved

Open Access in DiVA

fulltext(2149 kB)7 downloads
File information
File name FULLTEXT01.pdfFile size 2149 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Nazli, BilgicVulgari, Sofia Kiriaki
By organisation
Department of Computer Science
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 7 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 67 hits
ReferencesLink to record
Permanent link

Direct link