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Eye center localization and gaze gesture recognition for human-computer interaction

Zhang, Wenhao; Smith, Melvyn L.; Smith, Lyndon N.; Farooq, Abdul

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Authors

Dr Wenhao Zhang Wenhao.Zhang@uwe.ac.uk
Associate Professor of Computer Vision and Machine Learning

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

Abdul Farooq Abdul2.Farooq@uwe.ac.uk
Associate Director (Human-Centric Robotics)



Abstract

© 2016 Optical Society of America. This paper introduces an unsupervised modular approach for accurate and real-time eye center localization in images and videos, thus allowing a coarse-to-fine, global-to-regional scheme. The trajectories of eye centers in consecutive frames, i.e., gaze gestures, are further analyzed, recognized, and employed to boost the human-computer interaction (HCI) experience. This modular approach makes use of isophote and gradient features to estimate the eye center locations. A selective oriented gradient filter has been specifically designed to remove strong gradients from eyebrows, eye corners, and shadows, which sabotage most eye center localization methods. A real-world implementation utilizing these algorithms has been designed in the form of an interactive advertising billboard to demonstrate the effectiveness of our method for HCI. The eye center localization algorithm has been compared with 10 other algorithms on the BioID database and six other algorithms on the GI4E database. It outperforms all the other algorithms in comparison in terms of localization accuracy. Further tests on the extended Yale Face Database b and self-collected data have proved this algorithm to be robust against moderate head poses and poor illumination conditions. The interactive advertising billboard has manifested outstanding usability and effectiveness in our tests and shows great potential for benefiting a wide range of real-world HCI applications.

Citation

Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. (2016). Eye center localization and gaze gesture recognition for human-computer interaction. Journal of the Optical Society of America A, 33(3), 314-325. https://doi.org/10.1364/JOSAA.33.000314

Journal Article Type Article
Acceptance Date Dec 22, 2015
Online Publication Date Mar 1, 2016
Publication Date Mar 1, 2016
Deposit Date Feb 8, 2016
Publicly Available Date Apr 6, 2016
Journal Journal of the Optical Society of America A: Optics and Image Science, and Vision
Print ISSN 1084-7529
Electronic ISSN 1520-8532
Publisher Optical Society of America
Peer Reviewed Peer Reviewed
Volume 33
Issue 3
Pages 314-325
DOI https://doi.org/10.1364/JOSAA.33.000314
Keywords eye centre, gaze, human computer interaction
Public URL https://uwe-repository.worktribe.com/output/909554
Publisher URL http://dx.doi.org/10.1364/JOSAA.33.000314

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