Visual Multi-Metric Grouping of Eye-Tracking Data

  • Ayush Kumar Stony Brook University, New York
  • Rudolf Netzel University of Stuttgart
  • Michael Burch Eindhoven Uni. of Tech., Netherlands
  • Daniel Weiskopf University of Stuttgart
  • Klaus Mueller Stony Brook University, New York
Keywords: Eye movement, metrics, eye tracking, visualization, parallel coordinates, saccades, scanpath, similarity

Abstract

We present an algorithmic and visual grouping of participants and eye-tracking metrics derived from recorded eye-tracking data. Our method utilizes two well-established visualization concepts. First, parallel coordinates are used to provide an overview of the used metrics, their interactions, and similarities, which helps select suitable metrics that describe characteristics of the eye-tracking data. Furthermore, parallel coordinates plots enable an analyst to test the effects of creating a combination of a subset of metrics resulting in a newly derived eye-tracking metric. Second, a similarity matrix visualization is used to visually represent the affine combination of metrics utilizing an algorithmic grouping of subjects that leads to distinct visual groups of similar behavior. To keep the diagrams of the matrix visualization simple and understandable, we visually encode our eye- tracking data into the cells of a similarity matrix of participants. The algorithmic grouping is performed with a clustering based on the affine combination of metrics, which is also the basis for the similarity value computation of the similarity matrix. To illustrate the usefulness of our visualization, we applied it to an eye-tracking data set involving the reading behavior of metro maps of up to 40 participants. Finally, we discuss limitations and scalability issues of the approach focusing on visual and perceptual issues.

Author Biography

Ayush Kumar, Stony Brook University, New York

Phd Candidate,
Computer Science Deparment,
Stony Brook University

Published
14-02-2018
How to Cite
Kumar, A., Netzel, R., Burch, M., Weiskopf, D., & Mueller, K. (2017). Visual Multi-Metric Grouping of Eye-Tracking Data. Journal of Eye Movement Research, 10(5). https://doi.org/10.16910/jemr.10.5.10
Section
Special Thematic Issue "Eye Tracking and Visualization"