Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1111/cgf.13079 | COMPUTER GRAPHICS FORUM |
Keywords | Field | DocType |
eye tracking,visualization,survey | Computer vision,Information visualization,Computer science,Visualization,Visual analytics,Eye tracking,Artificial intelligence,Creative visualization | Journal |
Volume | Issue | ISSN |
36.0 | 8.0 | 0167-7055 |
Citations | PageRank | References |
18 | 0.87 | 37 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| T. Blascheck | 1 | 137 | 17.67 |
| Kuno Kurzhals | 2 | 227 | 20.63 |
| Michael Raschke | 3 | 134 | 9.83 |
| Michael Burch | 4 | 854 | 66.47 |
| Daniel Weiskopf | 5 | 2988 | 204.30 |
| Thomas Ertl | 6 | 4417 | 401.52 |