@InProceedings{MiguelOliveira2012,
author="Miguel Oliveira
and Angel Sappa
and V. Santos",
title="Color Correction for Onboard Multi-camera Systems  using 3D Gaussian Mixture Models",
booktitle="IEEE Intelligent Vehicles Symposium",
year="2012",
publisher="IEEE Xplore",
pages="299--303",
abstract="The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.",
optnote="ADAS",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2021), last updated on Fri, 23 Jun 2017 11:06:27 +0200",
isbn="978-1-4673-2119-8",
issn="1931-0587",
doi="10.1109/IVS.2012.6232141",
file=":http://refbase.cvc.uab.es/files/OSS2012b.pdf:PDF"
}