Talks and Poster Presentations (with Proceedings-Entry):
H. Liao, W. Dong, G. Gartner, H. Liu:
"Identifying User Tasks in Map Based-Pedestrian Navigation from Eye Tracking Data";
Talk: 14th International Conference on Location Based Services,
- 2018-01-17; in: "Adjunct Proceedings of the 14th International Conference on Location Based Services",
P. Kiefer, H. Huang, N. van de Weghe, M. Raubal (ed.);
Eye movement data convey a wealth of information that can be used to inspect human behavior and cognitive processes. In this study, we
explored to identify user tasks in map-based pedestrian navigation using eye movement data. We collected 44 participants´ eye movement data by conducting an eye tracking experiment in real-world environments. We trained and cross-validated a Random Forests classifier to classify 7 common user tasks using 564 features. The preliminary results show the classifier can achieve an overall accuracy of 48%.
wayfinding, eye movement, Random Forests
Created from the Publication Database of the Vienna University of Technology.