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Efficient Eye Corner and Gaze Detection for Sclera Recognition Under Relaxed Imaging Constraints

Lookup NU author(s): sinan Alkassar, Dr Wai Lok Woo, Professor Satnam Dlay, Professor Jonathon Chambers

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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 era 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.


Publication metadata

Author(s): Alkassar S, Woo WL, Dlay SS, Chambers JA

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 24th European Signal Processing Conference (EUSIPCO)

Year of Conference: 2016

Pages: 1965-1969

Print publication date: 01/01/2016

Online publication date: 01/12/2016

Acceptance date: 01/01/1900

ISSN: 2076-1465

Publisher: IEEE

URL: https://doi.org/10.1109/EUSIPCO.2016.7760592

DOI: 10.1109/EUSIPCO.2016.7760592

Library holdings: Search Newcastle University Library for this item

ISBN: 9780992862657


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