research-article

Improving hands-free menu selection using eyegaze glances and fixations

Authors:

M. Stella AtkinsAuthors Info & Claims

ETRA '08: Proceedings of the 2008 symposium on Eye tracking research & applications

Pages 47 - 50

https://doi.org/10.1145/1344471.1344482

Published: 26 March 2008 Publication History

Abstract

A real-time eyegaze selection interface was implemented using a Tobii eyegaze tracking monitor. A hierarchical button menu was displayed on the screen and specified selections were made by eyegaze fixations and glances on the menu widgets. The initial version tested three different spatial layouts of the menu widgets and employed a dwell + glance method of selection. Results from the pilot interface led to usability improvements in the second version of the interface. Selections were activated using a glance + dwell method. The usability of the second study interface received a positive response from all 8 participants. Each selection gained more than a 100% speed increase using the revised interface.

A more intuitive selection interface in the second study allowed us to test users selection accuracy at faster dwell selection thresholds. Users quickly learned to achieve accurate selections in 180 ms, but made errors when selections occurred in 150 ms.

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Cited By

Isomoto TYamanaka SShizuki B(2022)Dwell Selection with ML-based Intent Prediction Using Only Gaze DataProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35503016:3(1-21)Online publication date: 7-Sep-2022
https://dl.acm.org/doi/10.1145/3550301
Kim THam AAhn SLee G(2022)Lattice Menu: A Low-Error Gaze-Based Marking Menu Utilizing Target-Assisted Gaze Gestures on a Lattice of Visual AnchorsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501977(1-12)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501977
Ahn SSantosa SParent MWigdor DGrossman TGiordano MKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)StickyPie: A Gaze-Based, Scale-Invariant Marking Menu Optimized for AR/VRProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445297(1-16)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445297
Show More Cited By

Index Terms

Improving hands-free menu selection using eyegaze glances and fixations
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
      2. Computer vision tasks
        Scene understanding
    2. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

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Published In

cover image ACM Conferences

ETRA '08: Proceedings of the 2008 symposium on Eye tracking research & applications

March 2008

285 pages

ISBN:9781595939821

DOI:10.1145/1344471

Conference Chairs:
Kari-Jouko Räihä
University of Tampere, Finland
,
Andrew T. Duchowski
Clemson University, USA

Copyright © 2008 ACM.

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: 26 March 2008

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ETRA '08: Eye Tracking Research and Applications

March 26 - 28, 2008

Georgia, Savannah

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Cited By

Isomoto TYamanaka SShizuki B(2022)Dwell Selection with ML-based Intent Prediction Using Only Gaze DataProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35503016:3(1-21)Online publication date: 7-Sep-2022
https://dl.acm.org/doi/10.1145/3550301
Kim THam AAhn SLee G(2022)Lattice Menu: A Low-Error Gaze-Based Marking Menu Utilizing Target-Assisted Gaze Gestures on a Lattice of Visual AnchorsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501977(1-12)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501977
Ahn SSantosa SParent MWigdor DGrossman TGiordano MKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)StickyPie: A Gaze-Based, Scale-Invariant Marking Menu Optimized for AR/VRProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445297(1-16)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445297
Clemotte AVelasco MRaya RCeres Rde Córdoba RRocon E(2017)Metodología de Evaluación de Eye-trackers como Dispositivos de Acceso Alternativo para Personas con Parálisis CerebralRevista Iberoamericana de Automática e Informática Industrial RIAI10.1016/j.riai.2017.07.00414:4(384-393)Online publication date: Oct-2017
https://doi.org/10.1016/j.riai.2017.07.004

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