Novel Methods for Analysis and Visualization of Saccade Trajectories

Visualization of eye-tracking data is mainly based on fixations. However, saccade trajectories and their characteristics might contain more information than sole fixation positions. Artists, for example, can influence the way our eyes traverse a picture by employing composition methods. Repetitive saccade trajectories and the sequence of eye movements seem to correlate with this composition. In this work, we propose two novel methods to visualize saccade patterns during static stimulus viewing. The first approach, so-called saccade heatmap, utilizes a modified Gaussian density distribution to highlight frequent gaze paths. The second approach is based on clustering and assigns identical labels to similar saccades to thus filter for the most relevant gaze paths. We demonstrate and discuss the strengths and weaknesses of both approaches by examples of free-viewing paintings and compare them to other state-of-the-art visualization techniques.