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Variational reflectance estimation from multi-view images

Mélou, Jean and Quéau, Yvain and Durou, Jean-Denis and Castan, Fabien and Cremers, Daniel Variational reflectance estimation from multi-view images. (2018) Journal of Mathematical Imaging and Vision, 60 (9). 1527-1546. ISSN 0924-9907

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Official URL: https://doi.org/10.1007/s10851-018-0809-x

Abstract

We tackle the problem of reflectance estimation from a set of multi-view images, assuming known geometry. The approach we put forward turns the input images into reflectance maps, through a robust variational method. The variational model comprises an image-driven fidelity term and a term which enforces consistency of the reflectance estimates with respect to each view. If illumination is fixed across the views, then reflectance estimation remains under-constrained: a regularization term, which ensures piecewise-smoothness of the reflectance, is thus used. Reflectance is parameterized in the image domain, rather than on the surface, which makes the numerical solution much easier, by resorting to an alternating majorization-minimization approach. Experiments on both synthetic and real-world datasets are carried out to validate the proposed strategy.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Technische Universität München - TUM (GERMANY)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Mikros Image (FRANCE)
Laboratory name:
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Deposited On:25 Feb 2020 15:58

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