Publications in Scientific Journals:
P. Polatsek, M. Waldner, I. Viola et al.:
"Exploring visual attention and saliency modeling for task-based visual analysis";
Computers & Graphics (invited),
Memory, visual attention and perception play a critical role in the design of visualizations. The way users observe a visualization is affected by salient stimuli in a scene as well as by domain knowledge, interest, and the task. While recent saliency models manage to predict the usersī visual attention in visualizations during exploratory analysis, there is little evidence how much influence bottom-up saliency has on task-based visual analysis. Therefore, we performed an eye-tracking study with 47 users to determine the usersī path of attention when solving three low-level analytical tasks using 30 different charts from the MASSVIS database . We also compared our task-based eye tracking data to the data from the original memorability experiment by Borkin et al. . We found that solving a task leads to more consistent viewing patterns compared to exploratory visual analysis. However, bottom-up saliency of a visualization has negligible influence on usersī fixations and task efficiency when performing a low-level analytical task. Also, the efficiency of visual search for an extreme target data point is barely influenced by the targetīs bottom-up saliency. Therefore, we conclude that bottom-up saliency models tailored towards information visualization are not suitable for predicting visual attention when performing task-based visual analysis. We discuss potential reasons and suggest extensions to visual attention models to better account for task-based visual analysis.
Information visualization, Eye-tracking experiment, Saliency, Visual attention, Low-level analytical tasks
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.