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Visualization of Eye Tracking Data: A Taxonomy and Survey
Author(s) -
Blascheck T.,
Kurzhals K.,
Raschke M.,
Burch M.,
Weiskopf D.,
Ertl T.
Publication year - 2017
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.13079
Subject(s) - visualization , eye tracking , computer science , tracking (education) , information visualization , exploratory data analysis , data visualization , visual analytics , creative visualization , artificial intelligence , data science , computer vision , human–computer interaction , data mining , psychology , pedagogy
This survey provides an introduction into eye tracking visualization with an overview of existing techniques. Eye tracking is important for evaluating user behaviour. Analysing eye tracking data is typically done quantitatively, applying statistical methods. However, in recent years, researchers have been increasingly using qualitative and exploratory analysis methods based on visualization techniques. For this state‐of‐the‐art report, we investigated about 110 research papers presenting visualization techniques for eye tracking data. We classified these visualization techniques and identified two main categories: point‐based methods and methods based on areas of interest. Additionally, we conducted an expert review asking leading eye tracking experts how they apply visualization techniques in their analysis of eye tracking data. Based on the experts' feedback, we identified challenges that have to be tackled in the future so that visualizations will become even more widely applied in eye tracking research.