Efficient eye corner and gaze detection for sclera recognition under relaxed imaging constraints

Alkassar, S., Woo, Wai Lok, Dlay, Satnam and Chambers, Jonathon (2016) Efficient eye corner and gaze detection for sclera recognition under relaxed imaging constraints. In: EUSIPCO 2016 - 24th European Signal Processing Conference, 28th August - 2nd September 2016, Budapest, Hungary.

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Abstract

Sclera recognition has provoked research interest recently due to the distinctive properties of its blood vessels. However, segmenting noisy sclera areas in eye images under relaxed imaging constraints, such as different gaze directions, capturing on-the-move and at-a-distance, has not been extensively investigated. In our previous work, we proposed a novel method for sclera segmentation under unconstrained image conditions with a drawback being that the eye gaze direction is manually labeled for each image. Therefore, we propose a robust method for automatic eye corner and gaze detection. The proposed method involves two levels of eye corners verification to minimize eye corner point misclassification when noisy eye images are introduced. Moreover, gaze direction estimation is achieved through the pixel properties of the sclera area. Experimental results in on-the-move and at-a-distance contexts with multiple eye gaze directions using the UBIRIS.v2 database show a significant improvement in terms of accuracy and gaze detection rates.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Eyelids, Skin, Estimation, Iris, Europe, Signal processing, Databases
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	09 Apr 2019 08:50
Last Modified:	10 Oct 2019 20:16
URI:	http://nrl.northumbria.ac.uk/id/eprint/38846

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