@InProceedings{MarcSerra2012,
author="Marc Serra
and Olivier Penacchio
and Robert Benavente
and Maria Vanrell",
title="Names and Shades of Color for Intrinsic Image Estimation",
booktitle="25th IEEE Conference on Computer Vision and Pattern Recognition",
year="2012",
publisher="IEEE Xplore",
pages="278--285",
abstract="In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance.",
optnote="CIC",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2026), last updated on Fri, 14 Feb 2014 11:24:06 +0100",
isbn="978-1-4673-1226-4",
issn="1063-6919",
doi="10.1109/CVPR.2012.6247686",
opturl="http://ieeexplore.ieee.org/xpl/articleDetails.jsp? arnumber=6247686",
file=":http://refbase.cvc.uab.es/files/SPB2012a.pdf:PDF"
}