extended-abstract

Real time eye movement identification protocol

Authors:

Do Hyong Koh,

Sandeep Munikrishne Gowda,

Oleg V. KomogortsevAuthors Info & Claims

CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems

Pages 3499 - 3504

https://doi.org/10.1145/1753846.1754008

Published: 10 April 2010 Publication History

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Abstract

This paper introduces a Real Time Eye Movement Identification (REMI) protocol designed to address challenges related to the implementation of the eye-gaze guided computer interfaces. The REMI protocol provides the framework for 1) eye position data processing such as noise removal, smoothing, prediction and handling of invalid positional samples 2) real time eye movement identification into the basic eye movement types 3) mapping of the classified eye movement data to interface actions such as object selection.

References

[1]

Duchowski, A. T. Eye Tracking Methodology: Theory and Practice. Springer-Verlag, London, UK, 2007.

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Koh, D., Munikrishne Gowda, S., and Komogortsev, O. Input evaluation of an eye-gaze-guided interface: kalman filter vs. velocity threshold eye movement identification. In Proc. EICS 2009, ACM Press (2009), 197--202.

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[3]

Komogortsev, O. V., and Khan, J. Kalman filtering in the design of eye-gaze-guided computer interfaces. In Proc. HCII 2007, (2007), 679--689.

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[4]

Komogortsev, O. V., and Khan, J. I. Predictive real-time perceptual compression based on eye-gaze-position analysis. ACM Trans. Multimedia Comput. Commun. Appl., (2008), 4, 1--16.

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Komogortsev, O. V., and Khan, J. Eye movement prediction by Kalman filter with intergrated linear horizontal oculomotor plant mechanical model. In Proc. ETRA 2008, (2008), 229--236.

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Komogortsev, O. V., Ryu, Y., Koh, D., and Munikrishne Gowda, S. Instantaneous saccade driven eye gaze interaction. ACM International Conference on Advances in Computer Entertainment Technology, (2009).

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[7]

Komogortsev, O.V., Jayarathna, U. K. S., Koh, D. and Munikrishne Gowda, S. Qualitative and quantitative scoring and evaluation of the eye movement classification algorithms. In Proc. ETRA 2010, (2010).

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Sibert, L. E., and Jacob, R. J. K. Evaluation of eye gaze interaction. In Proc. SIGCHI conference on Human factors in computing systems 2000, ACM Press (2000), 281--288.

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Wobbrock, J. O., Rubinstein, J., Sawyer, M. W., and Duchowski, A. T. Longitudinal evaluation of discrete consecutive gaze gestures for text entry. In Proc. ETRA 2008, ACM Press (2008), 11--18.

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Cited By

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Suhari AHartanto RWibirama S(2023)Improving Performance of Eye Movements Classification Using CNN-Transformer Model2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA)10.1109/ICAMIMIA60881.2023.10427836(751-756)Online publication date: 14-Nov-2023
https://doi.org/10.1109/ICAMIMIA60881.2023.10427836
Elmadjian CGonzales CCosta RMorimoto C(2022)Online eye-movement classification with temporal convolutional networksBehavior Research Methods10.3758/s13428-022-01978-255:7(3602-3620)Online publication date: 11-Oct-2022
https://doi.org/10.3758/s13428-022-01978-2
Fikri MSantosa PWibirama S(2021)A Review on Opportunities and Challenges of Machine Learning and Deep Learning for Eye Movements Classification2021 IEEE International Biomedical Instrumentation and Technology Conference (IBITeC)10.1109/IBITeC53045.2021.9649434(65-70)Online publication date: 20-Oct-2021
https://doi.org/10.1109/IBITeC53045.2021.9649434
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Index Terms

Real time eye movement identification protocol
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interactive systems and tools

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Information & Contributors

Information

Published In

CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems

April 2010

2219 pages

ISBN:9781605589305

DOI:10.1145/1753846

General Chairs:
Elizabeth Mynatt
Georgia Institute of Technology
,
Don Schoner
Georgia Institute of Technology
,
Program Chairs:
Geraldine Fitzpatrick
Vienna University of Technology
,
Scott Hudson
Carnegie Mellon University
,
Keith Edwards
Georgia Tech
,
Tom Rodden
University of Nottingham

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 April 2010

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Extended-abstract

Conference

CHI '10

Sponsor:

SIGCHI

CHI '10: CHI Conference on Human Factors in Computing Systems

April 10 - 15, 2010

Georgia, Atlanta, USA

Acceptance Rates

CHI EA '10 Paper Acceptance Rate 350 of 1,346 submissions, 26%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

Upcoming Conference

CHI '25

Sponsor:
sigchi

CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

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Cited By

View all

Suhari AHartanto RWibirama S(2023)Improving Performance of Eye Movements Classification Using CNN-Transformer Model2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA)10.1109/ICAMIMIA60881.2023.10427836(751-756)Online publication date: 14-Nov-2023
https://doi.org/10.1109/ICAMIMIA60881.2023.10427836
Elmadjian CGonzales CCosta RMorimoto C(2022)Online eye-movement classification with temporal convolutional networksBehavior Research Methods10.3758/s13428-022-01978-255:7(3602-3620)Online publication date: 11-Oct-2022
https://doi.org/10.3758/s13428-022-01978-2
Fikri MSantosa PWibirama S(2021)A Review on Opportunities and Challenges of Machine Learning and Deep Learning for Eye Movements Classification2021 IEEE International Biomedical Instrumentation and Technology Conference (IBITeC)10.1109/IBITeC53045.2021.9649434(65-70)Online publication date: 20-Oct-2021
https://doi.org/10.1109/IBITeC53045.2021.9649434
Nuraini AMurnani SArdiyanto IWibirama S(2021)Machine Learning in Gaze-Based Interaction: A Survey of Eye Movements Events Detection2021 International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE)10.1109/COSITE52651.2021.9649646(150-155)Online publication date: 20-Oct-2021
https://doi.org/10.1109/COSITE52651.2021.9649646
Alfaroby E. MWibirama SArdiyanto I(2020)Accuracy Improvement of Object Selection in Gaze Gesture Application using Deep Learning2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)10.1109/ICITEE49829.2020.9271771(307-311)Online publication date: 6-Oct-2020
https://doi.org/10.1109/ICITEE49829.2020.9271771
Wibirama SMurnani SSetiawan NNurlatifa H(2020)A Survey of Event Detection Methods for Eye Movements Classification in Smooth-Pursuit-Based Interactive Applications2020 International Symposium on Community-centric Systems (CcS)10.1109/CcS49175.2020.9231384(1-6)Online publication date: Sep-2020
https://doi.org/10.1109/CcS49175.2020.9231384
Murnani SWibirama SSetiawan N(2019)Comparative Analysis of Signal Denoising Methods for Object Selection in Gaze-Based Interactive Applications2019 5th International Conference on Science and Technology (ICST)10.1109/ICST47872.2019.9166223(1-6)Online publication date: Jul-2019
https://doi.org/10.1109/ICST47872.2019.9166223
Ebeid IGwizdka JSharif BKrejtz K(2018)Real-time gaze transition entropyProceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications10.1145/3204493.3208340(1-3)Online publication date: 14-Jun-2018
https://dl.acm.org/doi/10.1145/3204493.3208340
Jalaliniya SMardanbegi DKaye JDruin ALampe CMorris DHourcade J(2016)EyeGripProceedings of the 2016 CHI Conference on Human Factors in Computing Systems10.1145/2858036.2858584(5801-5811)Online publication date: 7-May-2016
https://dl.acm.org/doi/10.1145/2858036.2858584
Vidal MBulling AGellersen HMorimoto CIstance HMulligan JQvarfordt P(2012)Detection of smooth pursuits using eye movement shape featuresProceedings of the Symposium on Eye Tracking Research and Applications10.1145/2168556.2168586(177-180)Online publication date: 28-Mar-2012
https://dl.acm.org/doi/10.1145/2168556.2168586
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