Wiśniewska, J, Rezaei, M orcid.org/0000-0003-3892-421X and Klette, R (2014) Robust Eye Gaze Estimation. In: Chmielewski, LJ, Kozera, R, Shin, B and Wojciechowski, K, (eds.) ICCVG 2014: Computer Vision and Graphics. International Conference on Computer Vision and Graphics, 15-17 Sep 2014, Warsaw, Poland. Springer Verlag , pp. 636-644. ISBN 9783319113302
Abstract
Eye gaze detection under challenging lighting conditions is a non-trivial task. Pixel intensity and the shades around the eye region may change depending on the time of day, location, or due to artificial lighting. This paper introduces a lighting-adaptive solution for robust eye gaze detection. First, we propose a binarization and cropping technique to limit our region of interest. Then we develop a gradient-based method for eye-pupil detection; and finally, we introduce an adaptive eye-corner detection technique that altogether lead to robust eye gaze estimation. Experimental results show the outperformance of the proposed method compared with related techniques.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer International Publishing Switzerland 2014. This is a post-peer-review, pre-copyedit version of an article published in ICCVG 2014: Computer Vision and Graphics . The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-11331-9_76 |
Keywords: | Corner Position; Fast Feature; Rapid Object Detection; Adaptive Binarization; Pupil Detection |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Mar 2020 14:58 |
Last Modified: | 19 Mar 2020 15:56 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/978-3-319-11331-9_76 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157585 |