Scan path visualization and comparison using visual aggregation techniques

Keywords: eye tracking, scanpath, saccades, visualization, fixation clustering, mean-shift, edge bundling, flow direction map, oriented line integral convolution


We demonstrate the use of different visual aggregation techniques to obtain non-cluttered visual representations of scanpaths. First, fixation points are clustered using the mean-shift algorithm. Second, saccades are aggregated using the Attribute-Driven Edge Bundling (ADEB) algorithm that handles a saccades direction, onset timestamp, magnitude or their combination for the edge compatibility criterion. Flow direction maps, computed during bundling, can be visualized separately (vertical or horizontal components) or as a single image using the Oriented Line Integral Convolution (OLIC) algorithm. Furthermore, cosine similarity between two flow direction maps provides a similarity map to compare two scanpaths. Last, we provide examples of basic patterns, visual search task, and art perception. Used together, these techniques provide valuable insights about scanpath exploration and informative illustrations of the eye movement data.

Author Biographies

Vsevolod Peysakhovich, ISAE-Supaéro
Research Scientist at DCAS, ISAE-Supaéro
Christophe Hurter, ENAC
Professor at ENAC
How to Cite
Peysakhovich, V., & Hurter, C. (2018). Scan path visualization and comparison using visual aggregation techniques. Journal of Eye Movement Research, 10(5).
Special Thematic Issue "Eye Tracking and Visualization"