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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents

ID: 420008.0, MPI für biologische Kybernetik / Biologische Kybernetik
Bayesian Color Constancy Revisited
Authors:Gehler, P.V.; Rother, C.; Blake, A.; Minka, T.; Sharp, T.
Date of Publication (YYYY-MM-DD):2008-06
Title of Proceedings:Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008)
Start Page:1
End Page:8
Physical Description:8
Audience:Not Specified
Intended Educational Use:No
Abstract / Description: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.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI f�r biologische Kybernetik/Empirical Inference (Dept. Sch�lkopf)
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