Eye center localization and gaze gesture recognition for human computer interaction

Zhang, W., Smith, M., Smith, L. and Farooq, A. (2016) Eye center localization and gaze gesture recognition for human computer interaction. Journal of the Optical Society of America A, 33 (3). pp. 314-325. ISSN 1084-7529 Available from: http://eprints.uwe.ac.uk/28148

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Publisher's URL: http://dx.doi.org/10.1364/JOSAA.33.000314


This paper introduces an unsupervised modular approach for accurate and real-time eye centre localisation in images and videos following a coarse-to-fine, global-to-regional scheme. The trajectories of eye centres in consecutive frames, i.e. gaze gestures, are further analysed, recognised and employed to boost human computer interaction (HCI) experience. This modular approach makes use of isophote and gradient features to estimate the eye centre locations. A Selective Oriented Gradient (SOG) filter has been specifically designed to remove strong gradients from eyebrows, eye corners and shadows, which sabotage most eye centre localisation methods. A real-world implementation utilising these algorithms has been designed in the form of an interactive advertising billboard to demonstrate the effectiveness of our method for HCI. The eye centre localisation algorithm has been compared with 10 other algorithms on the BioID database and 6 other algorithms on the GI4E database. It outperforms all the other algorithms in comparison in terms of localisation 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 in benefiting a wide range of real-world HCI applications.

Item Type:Article
Uncontrolled Keywords:eye centre, gaze, human computer interaction
Faculty/Department:Faculty of Environment and Technology > Department of Engineering Design and Mathematics
ID Code:28148
Deposited By: W. Zhang
Deposited On:08 Feb 2016 08:49
Last Modified:11 Apr 2016 19:44

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