A variational approach to shape-from-shading under natural illumination

Quéau Y, Mélou J, Castan F, Cremers D, Durou JD (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 10746 LNCS

Pages Range: 342-357

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Venice, ITA

ISBN: 9783319781983

DOI: 10.1007/978-3-319-78199-0_23

Abstract

A numerical solution to shape-from-shading under natural illumination is presented. It builds upon an augmented Lagrangian approach for solving a generic PDE-based shape-from-shading model which handles directional or spherical harmonic lighting, orthographic or perspective projection, and greylevel or multi-channel images. Real-world applications to shading-aware depth map denoising, refinement and completion are presented.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Université Fédérale de Toulouse Midi-Pyrénées FR France (FR) Mikros Image FR France (FR)

How to cite

APA:

Quéau, Y., Mélou, J., Castan, F., Cremers, D., & Durou, J.D. (2018). A variational approach to shape-from-shading under natural illumination. In Marcello Pelillo, Edwin Hancock (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 342-357). Venice, ITA: Springer Verlag.

MLA:

Quéau, Yvain, et al. "A variational approach to shape-from-shading under natural illumination." Proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMVCPR 2017, Venice, ITA Ed. Marcello Pelillo, Edwin Hancock, Springer Verlag, 2018. 342-357.

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