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.
|Title of host publication
|Proceedings of the 2nd Workshop on Eye Tracking and Visualization, ETVIS 2016
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2017 Feb 10
|2nd Workshop on Eye Tracking and Visualization, ETVIS 2016 - Baltimore, United States
Duration: 2016 Oct 23 → …
|2nd Workshop on Eye Tracking and Visualization, ETVIS 2016
|16/10/23 → …
- 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