DocumentCode
62837
Title
Eye Tracking for Personal Visual Analytics
Author
Kurzhals, Kuno ; Weiskopf, Daniel
Author_Institution
Univ. of Stuttgart, Stuttgart, Germany
Volume
35
Issue
4
fYear
2015
fDate
July-Aug. 2015
Firstpage
64
Lastpage
72
Abstract
In many research fields, eye tracking has become an established method to analyze the distribution of visual attention in various scenarios. In the near future, eye tracking is expected to become ubiquitous, recording massive amounts of data in everyday situations. To make use of this data, new approaches for personal visual analytics will be necessary to make the data accessible, allowing nonexpert users to re-experience interesting events and benefit from self-reflection. This article discusses how eye tracking fits in the context of personal visual analytics, the challenges that arise with its application to everyday situations, and the research perspectives of personal eye tracking. As an example, the authors present a technique for representing areas of interest (AOIs) from multiple videos: the AOI cloud. They apply this technique to examine a user´s personal encounters with other people.
Keywords
gaze tracking; video signal processing; AOI cloud; areas of interest; personal eye tracking; personal visual analytics; visual attention distribution; Data visualization; Glass; Mobile communication; Semantics; Videos; Visual analytics; computer graphics; eye tracking; personal visual analytics; video visualization;
fLanguage
English
Journal_Title
Computer Graphics and Applications, IEEE
Publisher
ieee
ISSN
0272-1716
Type
jour
DOI
10.1109/MCG.2015.47
Filename
7106388
Link To Document