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  Bayesian Color Constancy Revisited

Gehler, P., Rother, C., Blake, A., Minka, T., & Sharp, T. (2008). Bayesian Color Constancy Revisited. In 2008 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-8). Piscataway, NJ, USA: IEEE.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C8F1-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-4312-D
Genre: Conference Paper

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 Creators:
Gehler, PV1, 2, Author              
Rother, C, Author
Blake, A, Author
Minka, T, Author
Sharp, T, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Computational color constancy is the task of estimating the true reflectances of visible surfaces in an image. In this paper we follow a line of research that assumes uniform illumination of a scene, and that the principal step in estimating reflectances is the estimation of the scene illuminant. We review recent approaches to illuminant estimation, firstly those based on formulae for normalisation of the reflectance distribution in an image — so-called grey-world algorithms, and those based on a Bayesian formulation of image formation. In evaluating these previous approaches we introduce a new tool in the form of a database of 568 high-quality, indoor and outdoor images, accurately labelled with illuminant, and preserved in their raw form, free of correction or normalisation. This has enabled us to establish several properties experimentally. Firstly automatic selection of grey-world algorithms according to image properties is not nearly so effective as has been thought. Secondly, it is shown that Bayesian illuminant estimation is significantly improved by the improved accuracy of priors for illuminant and reflectance that are obtained from the new dataset.

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 Dates: 2008-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/CVPR.2008.4587765
BibTex Citekey: 5098
 Degree: -

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Title: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008)
Place of Event: Anchorage, AK, USA
Start-/End Date: 2008-06-23 - 2008-06-28

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Title: 2008 IEEE Conference on Computer Vision and Pattern Recognition
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 8 Identifier: ISBN: 978-1-4244-2243-2