research-article

Evaluation of Appearance-Based Methods and Implications for Gaze-Based Applications

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Andreas BullingAuthors Info & Claims

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: 416, Pages 1 - 13

https://doi.org/10.1145/3290605.3300646

Published: 02 May 2019 Publication History

Abstract

Appearance-based gaze estimation methods that only require an off-the-shelf camera have significantly improved but they are still not yet widely used in the human-computer interaction (HCI) community. This is partly because it remains unclear how they perform compared to model-based approaches as well as dominant, special-purpose eye tracking equipment. To address this limitation, we evaluate the performance of state-of-the-art appearance-based gaze estimation for interaction scenarios with and without personal calibration, indoors and outdoors, for different sensing distances, as well as for users with and without glasses. We discuss the obtained findings and their implications for the most important gaze-based applications, namely explicit eye input, attentive user interfaces, gaze-based user modelling, and passive eye monitoring. To democratise the use of appearance-based gaze estimation and interaction in HCI, we finally present OpenGaze (www.opengaze.org), the first software toolkit for appearance-based gaze estimation and interaction.

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Cited By

Kennel KIshimaru SKüchemann SSteinert SKuhn JRuzika S(2025)Gaze-Based Prediction of Students’ Math Difficulties - A Time Dynamic Machine Learning Approach to Enable Early Individual AssistanceInternational Journal of Artificial Intelligence in Education10.1007/s40593-024-00447-5Online publication date: 22-Jan-2025
https://doi.org/10.1007/s40593-024-00447-5
Hagihara HZaadnoordijk LCusack RKimura NTsuji S(2024)Exploration of factors affecting webcam-based automated gaze codingBehavior Research Methods10.3758/s13428-024-02424-156:7(7374-7390)Online publication date: 1-May-2024
https://doi.org/10.3758/s13428-024-02424-1
Anh NBach NTu NKamioka ETan P(2024)SVD-Based Mind-Wandering Prediction from Facial Videos in Online LearningJournal of Imaging10.3390/jimaging1005009710:5(97)Online publication date: 24-Apr-2024
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Index Terms

Evaluation of Appearance-Based Methods and Implications for Gaze-Based Applications
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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cover image ACM Conferences

CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

9077 pages

ISBN:9781450359702

DOI:10.1145/3290605

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

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https://doi.org/10.1007/s40593-024-00447-5
Hagihara HZaadnoordijk LCusack RKimura NTsuji S(2024)Exploration of factors affecting webcam-based automated gaze codingBehavior Research Methods10.3758/s13428-024-02424-156:7(7374-7390)Online publication date: 1-May-2024
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Anh NBach NTu NKamioka ETan P(2024)SVD-Based Mind-Wandering Prediction from Facial Videos in Online LearningJournal of Imaging10.3390/jimaging1005009710:5(97)Online publication date: 24-Apr-2024
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Hisadome YWu TQin JSugano Y(2024)Rotation-Constrained Cross-View Feature Fusion for Multi-View Appearance-based Gaze Estimation2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00588(5973-5982)Online publication date: 3-Jan-2024
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