Data-driven approaches to unrestricted gaze-Tracking benefit from saccade filtering

Nina Flad, Jonas C. Ditz, Albrecht Schmidt, Heinrich Bulthoff, Lewis L. Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Unrestricted gaze tracking that allows for head and body movements can enable us to understand interactive gaze behavior with large-scale visualizations. Approaches that support this, by simultaneously recording eye-And user-movements, can either be based on geometric or data-driven regression models. A data-driven approach can be implemented more flexibly but its performance can suffer with poor quality training data. In this paper, we introduce a pre-processing procedure to remove training data for periods when the gaze is not fixating the presented target stimuli. Our procedure is based on a velocity-based filter for rapid eye-movements (i.e., saccades). Our results show that this additional procedure improved the accuracy of our unrestricted gaze-Tracking model by as much as 56 %. Future improvements to data-driven approaches for unrestricted gaze-Tracking are proposed, in order to allow for more complex dynamic visualizations.

Original languageEnglish
Title of host publicationProceedings of the 2nd Workshop on Eye Tracking and Visualization, ETVIS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509047314
DOIs
Publication statusPublished - 2017 Feb 10
Externally publishedYes
Event2nd Workshop on Eye Tracking and Visualization, ETVIS 2016 - Baltimore, United States
Duration: 2016 Oct 23 → …

Other

Other2nd Workshop on Eye Tracking and Visualization, ETVIS 2016
CountryUnited States
CityBaltimore
Period16/10/23 → …

Keywords

  • J.2 [computer applications]: physical sciences and engineering-engineering
  • J.4 [computer applications]: social and behavioral sciences-psychology

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Media Technology

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