Implicit Gaze Interaction for Information Visualization


Feiyang Wang


This thesis presents a novel marker-free method for identifying screens of interest when using head-mounted eye-tracking for visualization in cluttered and multi-screen environments. The presented approach offers a solution for discerning visualization entities from sparse back-
grounds by incorporating edge-detection into the existing pipeline. The system allows for both more efficient screen identification and improved accuracy over the state-of-the-art ORB algorithm. To make use of this pipeline in visualization applications, a model is introduced to track a user’s interest in rendered visualization objects by collecting the gaze data and calculating the object group’s interest scores across selected visual features. With the interest model, We offer an implicit gaze interaction system that provides subtle interaction supports to improve group-of-interest objects visibility and to ease object selection in crowded regions of information visualizations.

Keywords: gaze estimation; feature detection; attention modelling; implicit interaction; over-
plotting visualization


  • [IMG]
    F. Wang, “Implicit Gaze Interaction for Information Visualization,” Master Thesis, 2021.
    [Bibtex] [PDF]

      author={Feiyang Wang},
      title={Implicit Gaze Interaction for Information Visualization},
      school={University of Ontario Institute of Technology},


Christopher M. Collins

Associate Professor, Lab Director

Implicit Gaze Interaction for Information Visualization

Alexie Linardatos


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