research-article

Parallax error in the monocular head-mounted eye trackers

Authors:

Diako Mardanbegi,

Dan Witzner HansenAuthors Info & Claims

UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Pages 689 - 694

https://doi.org/10.1145/2370216.2370366

Published: 05 September 2012 Publication History

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Abstract

This paper investigates the parallax error, which is a common problem of many video-based monocular mobile gaze trackers. The parallax error is defined and described using the epipolar geometry in a stereo camera setup. The main parameters that change the error are introduced and it is shown how each parameter affects the error. The optimum distribution of the error (magnitude and direction) in the field of view varies for different applications. However, the results can be used for finding the optimum parameters that are needed for designing a head-mounted gaze tracker. It has been shown that the difference between the visual and optical axes does not have a significant effect on the parallax error, and the epipolar geometry can be used for describing the parallax error in the HMGT.

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Fu XFranchak JMacNeill LGunther KBorjon JYurkovic-Harding JHarding SBradshaw JPérez-Edgar K(2024)Implementing mobile eye tracking in psychological research: A practical guideBehavior Research Methods10.3758/s13428-024-02473-656:8(8269-8288)Online publication date: 15-Aug-2024
https://doi.org/10.3758/s13428-024-02473-6
Huang ZDuan XZhu GZhang SWang RWang Z(2024)Assessing the data quality of AdHawk MindLink eye-tracking glassesBehavior Research Methods10.3758/s13428-023-02310-256:6(5771-5787)Online publication date: 2-Jan-2024
https://doi.org/10.3758/s13428-023-02310-2
Fischer Jvan der Merwe JVandenheever D(2024)The Influence that the Complexity of the Three-Dimensional Eye Model Used to Generate Simulated Eye-tracking Data Has on the Gaze Estimation Errors Achieved Using the DataACM Transactions on Applied Perception10.1145/366063722:1(1-16)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3660637
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Index Terms

Parallax error in the monocular head-mounted eye trackers
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition

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Published In

UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing

September 2012

1268 pages

ISBN:9781450312240

DOI:10.1145/2370216

General Chair:
Anind K. Dey
Carnegie Mellon University
,
Program Chairs:
Hao-Hua Chu
National Taiwan University, Taiwan
,
Gillian Hayes
University of California, Irvine

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 05 September 2012

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Ubicomp '12: The 2012 ACM Conference on Ubiquitous Computing

September 5 - 8, 2012

Pennsylvania, Pittsburgh

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UbiComp '12 Paper Acceptance Rate 58 of 301 submissions, 19%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Fu XFranchak JMacNeill LGunther KBorjon JYurkovic-Harding JHarding SBradshaw JPérez-Edgar K(2024)Implementing mobile eye tracking in psychological research: A practical guideBehavior Research Methods10.3758/s13428-024-02473-656:8(8269-8288)Online publication date: 15-Aug-2024
https://doi.org/10.3758/s13428-024-02473-6
Huang ZDuan XZhu GZhang SWang RWang Z(2024)Assessing the data quality of AdHawk MindLink eye-tracking glassesBehavior Research Methods10.3758/s13428-023-02310-256:6(5771-5787)Online publication date: 2-Jan-2024
https://doi.org/10.3758/s13428-023-02310-2
Fischer Jvan der Merwe JVandenheever D(2024)The Influence that the Complexity of the Three-Dimensional Eye Model Used to Generate Simulated Eye-tracking Data Has on the Gaze Estimation Errors Achieved Using the DataACM Transactions on Applied Perception10.1145/366063722:1(1-16)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3660637
Thorsson MGalazka MÅsberg Johnels JHadjikhani N(2024)Influence of autistic traits and communication role on eye contact behavior during face-to-face interactionScientific Reports10.1038/s41598-024-58701-814:1Online publication date: 8-Apr-2024
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Velisar AShanidze N(2023)Noise estimation for head-mounted 3D binocular eye tracking using Pupil Core eye-tracking gogglesBehavior Research Methods10.3758/s13428-023-02150-056:1(53-79)Online publication date: 27-Jun-2023
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Xia YLiang JLi QXin PZhang N(2022)High-Accuracy 3D Gaze Estimation with Efficient Recalibration for Head-Mounted Gaze Tracking SystemsSensors10.3390/s2212435722:12(4357)Online publication date: 8-Jun-2022
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Hunt RBlackmore TMills CDicks M(2022)Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measuresi-Perception10.1177/2041669522111665213:5Online publication date: 26-Sep-2022
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