Sankeye: A Visualization Technique for AOI Transitions

Michael Burch, Neil Neal Timmermans

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Visually exploring AOI transitions aggregated from a group of eye tracked people is a challenging task. Many visualizations typically produce visual clutter or aggregate the temporal or visit order information in the data hiding the visual task solution strategies for the observer. In this paper we introduce the Sankeye technique that is based on the visual metaphor of Sankey diagrams applied to eye movement data, hence the name Sankeye. The technique encodes the frequencies of AOI transitions into differently thick rivers and subrivers. The distributions of the AOI transitions are visually represented by splitting and merging subrivers in a left-to-right reading direction. The technique allows to interactively adapt the number of predefined AOIs as well as the transition frequency number threshold with the goal to derive patterns and insights from eye movement data.
Original languageEnglish
Title of host publicationETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
Pages 1–5
ISBN (Electronic)9781450371346
ISBN (Print)978-1-4503-7134-6
DOIs
Publication statusPublished - Jun 2020
EventETRA 2020 ACM Symposium on Eye Tracking Research and Applications - Stuttgart, Germany
Duration: 2 Jun 20205 Jun 2020
https://etra.acm.org/2020/#:~:text=About%20ETRA%202020%3A,under%20the%20motto%20Bridging%20Communities.

Conference

ConferenceETRA 2020 ACM Symposium on Eye Tracking Research and Applications
Abbreviated titleETRA 2020
CountryGermany
CityStuttgart
Period2/06/205/06/20
Internet address

Keywords

  • Areas of interest
  • Eye tracking
  • Information visualization
  • Sankey diagrams
  • Transition matrices

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