Eye-tracking based adaptive parallel coordinates

Mohammad Chegini, Keith Andrews, Tobias Schreck, Alexei Sourin

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


Parallel coordinates is a well-known technique for visual analysis of high-dimensional data. Although it is effective for interactive discovery of patterns in subsets of dimensions and data records, it also has scalability issues for large datasets. In particular, the amount of visual information potentially being shown in a parallel coordinates plot grows combinatorially with the number of dimensions. Choosing the right ordering of axes is crucial, and poor design can lead to visual noise and a cluttered plot. In this case, the user may overlook a significant pattern, or leave some dimensions unexplored. In this work, we demonstrate how eye-tracking can help an analyst efficiently and effectively reorder the axes in a parallel coordinates plot. Implicit input from an inexpensive eye-tracker assists the system in finding unexplored dimensions. Using this information, the system guides the user either visually or automatically to find further appropriate orderings of the axes.

Original languageEnglish
Title of host publicationSIGGRAPH Asia 2019 Posters, SA 2019
PublisherAssociation of Computing Machinery
ISBN (Electronic)9781450369435
Publication statusPublished - 17 Nov 2019
EventSIGGRAPH Asia 2019 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2019 - Brisbane, Australia
Duration: 17 Nov 201920 Nov 2019

Publication series

NameSIGGRAPH Asia 2019 Posters, SA 2019


ConferenceSIGGRAPH Asia 2019 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2019


  • Adaptive user interfaces
  • Eye-tracking
  • Parallel coordinates

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design
  • Software


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