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Journal of Mathematical Imaging and Vision

, Volume 60, Issue 9, pp 1527–1546 | Cite as

Variational Reflectance Estimation from Multi-view Images

  • Jean Mélou
  • Yvain Quéau
  • Jean-Denis Durou
  • Fabien Castan
  • Daniel Cremers
Article
  • 133 Downloads

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.

Keywords

Reflectance Multi-view Shading Variational methods 

Notes

Acknowledgements

Yvain Quéau and Daniel Cremers were supported by the ERC Consolidator Grant “3D Reloaded.”

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.IRIT, UMR CNRS 5505, Université de ToulouseToulouseFrance
  2. 2.Mikros ImageLevallois-PerretFrance
  3. 3.Department of Computer ScienceTechnical University of MunichGarchingGermany

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