@InProceedings{OnurFerhat2015,
author="Onur Ferhat
and Arcadi Llanza
and Fernando Vilari{\~n}o",
title="A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios",
booktitle="Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015",
year="2015",
publisher="Springer International Publishing",
volume="9117",
pages="569--576",
optkeywords="Eye tracking",
optkeywords="Gaze estimation",
optkeywords="Natural light",
optkeywords="Webcam",
abstract="We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance--based/model--based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 \% in the horizontal direction and by 12 \% in the vertical direction compared to the baseline system.",
optnote="MV;SIAI",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2646), last updated on Thu, 12 May 2016 13:47:17 +0200",
isbn="978-3-319-19389-2",
issn="0302-9743",
doi="10.1007/978-3-319-19390-8_64"
}