Gazeprojector: accurate gaze estimation and seamless gaze interaction across multiple displays

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Christian Lander, Sven Gehring, Antonio Krüger, Sebastian Boring, Andreas Bulling

Mobile gaze-based interaction with multiple displays may occur from arbitrary positions and orientations. However, maintaining high gaze estimation accuracy in such situations remains a significant challenge. In this paper, we present GazeProjector, a system that combines (1) natural feature tracking on displays to determine the mobile eye tracker?s position relative to a display with (2) accurate point-of-gaze estimation. GazeProjector allows for seamless gaze estimation and interaction on multiple displays of arbitrary sizes independently of the user?s position and orientation to the display. In a user study with 12 participants we compare GazeProjector to established methods (here: visual on-screen markers and a state-of-the-art video-based motion capture system). We show that our approach is robust to varying head poses, orientations, and distances to the display, while still providing high gaze estimation accuracy across multiple displays without re-calibration for each variation. Our system represents an important step towards the vision of pervasive gaze-based interfaces.

Original languageEnglish
Title of host publicationUIST '15 Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology
Number of pages10
PublisherAssociation for Computing Machinery
Publication date2015
Pages395-404
ISBN (Electronic)978-1-4503-3779-3
DOIs
Publication statusPublished - 2015
Event28th Annual ACM Symposium on User Interface Software and Technology, UIST 2015 - Charlotte, United States
Duration: 8 Nov 201511 Nov 2015

Conference

Conference28th Annual ACM Symposium on User Interface Software and Technology, UIST 2015
LandUnited States
ByCharlotte
Periode08/11/201511/11/2015
SponsorACM SIGCHI, ACM SIGGRAPH

    Research areas

  • Calibration, Eye tracking, Gaze estimation, Large displays, Multi-display environments, Natural feature tracking

ID: 159819296