by Wísniewska, J, Rezaei, M and Klette, R
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.
Reference:
Robust eye gaze estimation (Wísniewska, J, Rezaei, M and Klette, R), In Computer Vision and Graphics, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, volume 8671, 2014.
Bibtex Entry:
@inproceedings{wsniewska2014robustestimation,
author = "Wísniewska, J and Rezaei, M and Klette, R",
booktitle = "Computer Vision and Graphics, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
organization = "Warsaw",
pages = "636--644",
publisher = "Springer Verlag",
title = "Robust eye gaze estimation",
volume = "8671",
year = "2014",
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.",
startyear = "2014",
startmonth = "Sep",
startday = "15",
finishyear = "2014",
finishmonth = "Sep",
finishday = "17",
issn = "0302-9743",
eissn = "1611-3349",
language = "eng",
conference = "International Conference in Computer Vision and Graphics",
}