abstract

Motion tracking of iris features for eye tracking

Author:

Aayush K. ChaudharyAuthors Info & Claims

ETRA '19: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications

Article No.: 53, Pages 1 - 3

https://doi.org/10.1145/3314111.3322872

Published: 25 June 2019 Publication History

Abstract

Current video-based eye trackers fail to acquire a high signal-to-noise (SNR) ratio which is crucial for specific applications like interactive systems, event detection, the study of various eye movements, and most importantly estimating the gaze position with high certainty. Specifically, current video-based eye trackers over-rely on precise localization of the pupil boundary and/or corneal reflection (CR) for gaze tracking, which often results in inaccuracies and large sample-to-sample root mean square (RMS-S2S). Therefore, it is crucial to address the shortcomings of these trackers, and we plan to study a new video-based eye tracking methodology focused on simultaneously tracking the motion of many iris features and investigate its implications for obtaining high accuracy and precision. In our preliminary work, the method has shown great potential for robust detection of microsaccades over 0.2 degrees with high confidence. Hence, we plan to explore and optimize this technique.

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Cited By

Barkevich KBailey RDiaz G(2024)Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual RealityProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36547057:2(1-16)Online publication date: 17-May-2024
https://dl.acm.org/doi/10.1145/3654705
Maus NRutledge DAl-Khazraji SBailey RAlm CShinohara KBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Gaze-guided Magnification for Individuals with Vision ImpairmentsExtended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3334480.3382995(1-8)Online publication date: 25-Apr-2020
https://doi.org/10.1145/3334480.3382995

Index Terms

Motion tracking of iris features for eye tracking
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction techniques

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Published In

cover image ACM Conferences

ETRA '19: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications

June 2019

623 pages

ISBN:9781450367097

DOI:10.1145/3314111

Conference Chairs:
Krzysztof Krejtz
SWPS University, Poland
,
Bonita Sharif
University of Nebraska-Lincoln

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 25 June 2019

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Frederick Wiedmain Endowment

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ETRA '19

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ETRA '19: 2019 Symposium on Eye Tracking Research and Applications

June 25 - 28, 2019

Colorado, Denver

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Overall Acceptance Rate 69 of 137 submissions, 50%

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Cited By

Barkevich KBailey RDiaz G(2024)Using Deep Learning to Increase Eye-Tracking Robustness, Accuracy, and Precision in Virtual RealityProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36547057:2(1-16)Online publication date: 17-May-2024
https://dl.acm.org/doi/10.1145/3654705
Maus NRutledge DAl-Khazraji SBailey RAlm CShinohara KBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Gaze-guided Magnification for Individuals with Vision ImpairmentsExtended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3334480.3382995(1-8)Online publication date: 25-Apr-2020
https://doi.org/10.1145/3334480.3382995

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