Eye centre localisation: An unsupervised modular approach

Zhang, W., Smith, M., Smith, L. and Farooq, A. (2016) Eye centre localisation: An unsupervised modular approach. Sensor Review, 36 (3). pp. 277-286. ISSN 0260-2288 Available from: http://eprints.uwe.ac.uk/28437

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Purpose – This paper introduces an unsupervised modular approach for eye centre localisation in images and videos following a coarse-to-fine, global-to-regional scheme. The design of the algorithm aims at excellent accuracy, robustness and real-time performance for use in real-world applications. Design/methodology/approach – A modular approach has been designed that makes use of isophote and gradient features to estimate eye centre locations. This approach embraces two main modalities that progressively reduce global facial features to local levels for more precise inspections. A novel Selective Oriented Gradient (SOG) filter has been specifically designed to remove strong gradients from eyebrows, eye corners and self-shadows, which sabotage most eye centre localisation methods. The proposed algorithm, tested on the BioID database, has shown superior accuracy. Findings – The eye centre localisation algorithm has been compared with 11 other methods on the BioID database and 6 other methods on the GI4E database. The proposed algorithm has outperformed all the other algorithms in comparison in terms of localisation accuracy while exhibiting excellent real-time performance. This method is also inherently robust against head poses, partial eye occlusions and shadows. Originality/value – The eye centre localisation method utilises two mutually complementary modalities as a novel, fast, accurate and robust approach. In addition, other than assisting eye centre localisation, the SOG filter is able to resolve general tasks regarding the detection of curved shapes. From an applied point of view, the proposed method has great potentials in benefiting a wide range of real-world HCI applications.

Item Type:Article
Additional Information:The published version of this article is available at http://www.emeraldinsight.com/doi/abs/10.1108/SR-06-2015-0098
Uncontrolled Keywords:eyes
Faculty/Department:Faculty of Environment and Technology > Department of Engineering Design and Mathematics
ID Code:28437
Deposited By: Dr W. Zhang
Deposited On:14 Mar 2016 16:33
Last Modified:01 Jul 2017 07:47

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