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Wearable eye tracker calibration at your fingertips

Published: 14 June 2018 Publication History

Abstract

Common calibration techniques for head-mounted eye trackers rely on markers or an additional person to assist with the procedure. This is a tedious process and may even hinder some practical applications. We propose a novel calibration technique which simplifies the initial calibration step for mobile scenarios. To collect the calibration samples, users only have to point with a finger to various locations in the scene. Our vision-based algorithm detects the users' hand and fingertips which indicate the users' point of interest. This eliminates the need for additional assistance or specialized markers. Our approach achieves comparable accuracy to similar marker-based calibration techniques and is the preferred method by users from our study. The implementation is openly available as a plugin for the open-source Pupil eye tracking platform.

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References

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Cited By

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  • (2025)The fundamentals of eye tracking part 4: Tools for conducting an eye tracking studyBehavior Research Methods10.3758/s13428-024-02529-757:1Online publication date: 6-Jan-2025
  • (2024)Calibration-Free Mobile Eye-Tracking Using Corneal ImagingSensors10.3390/s2404123724:4(1237)Online publication date: 15-Feb-2024
  • (2022)3D Gaze Estimation Using RGB-IR CamerasSensors10.3390/s2301038123:1(381)Online publication date: 29-Dec-2022
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cover image ACM Conferences
ETRA '18: Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications
June 2018
595 pages
ISBN:9781450357067
DOI:10.1145/3204493
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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Publication History

Published: 14 June 2018

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Author Tags

  1. calibration
  2. eye tracking
  3. head-mounted eye tracker

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ETRA '18

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Overall Acceptance Rate 69 of 137 submissions, 50%

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Cited By

View all
  • (2025)The fundamentals of eye tracking part 4: Tools for conducting an eye tracking studyBehavior Research Methods10.3758/s13428-024-02529-757:1Online publication date: 6-Jan-2025
  • (2024)Calibration-Free Mobile Eye-Tracking Using Corneal ImagingSensors10.3390/s2404123724:4(1237)Online publication date: 15-Feb-2024
  • (2022)3D Gaze Estimation Using RGB-IR CamerasSensors10.3390/s2301038123:1(381)Online publication date: 29-Dec-2022
  • (2020)EMOProceedings of the 18th International Conference on Mobile Systems, Applications, and Services10.1145/3386901.3388917(448-461)Online publication date: 15-Jun-2020
  • (2020)3D Gaze Estimation for Head-Mounted Devices based on Visual Saliency2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9341755(10611-10616)Online publication date: 24-Oct-2020
  • (2020)Towards Robust Auto-calibration for Head-mounted Gaze Tracking Systems2020 IEEE International Conference on Mechatronics and Automation (ICMA)10.1109/ICMA49215.2020.9233571(588-593)Online publication date: 13-Oct-2020
  • (2020)3D Gaze Estimation for Head-Mounted Eye Tracking System With Auto-Calibration MethodIEEE Access10.1109/ACCESS.2020.29996338(104207-104215)Online publication date: 2020
  • (2019)Improving eye-tracking calibration accuracy using symbolic regressionPLOS ONE10.1371/journal.pone.021367514:3(e0213675)Online publication date: 15-Mar-2019
  • (2019)mobEYEleAdjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers10.1145/3341162.3350842(1113-1119)Online publication date: 9-Sep-2019

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