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.

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This work deals with eye tracking systems and possibility of using them for control of many software or hardware devices. Project explains eye anatomy and electrophysiology, types of eye trackers and methods of eye tracking. We studied methods of image processing and image analyzing in LabVIEW development system and IMAQ Vision subsystem. On the base of these studies, we created whole eye tracking system .This system can be used for both the eye tracking from video recording and real time eye tracking. This system can monitor position or trajectory of look.