A non-convex variational approach to photometric stereo under inaccurate lighting
Queau Y, Wu T, Lauze F, Durou JD, Cremers D (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2017-January
Pages Range: 350-359
Conference Proceedings Title: Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
Event location: Honolulu, HI, USA
ISBN: 9781538604571
DOI: 10.1109/CVPR.2017.45
Abstract
This paper tackles the photometric stereo problem in the presence of inaccurate lighting, obtained either by calibration or by an uncalibrated photometric stereo method. Based on a precise modeling of noise and outliers, a robust variational approach is introduced. It explicitly accounts for self-shadows, and enforces robustness to castshadows and specularities by resorting to redescending Mestimators. The resulting non-convex model is solved by means of a computationally efficient alternating reweighted least-squares algorithm. Since it implicitly enforces integrability, the new variational approach can refine both the intensities and the directions of the lighting.
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
University of Copenhagen
Denmark (DK)
Université Fédérale de Toulouse Midi-Pyrénées
France (FR)
Germany (DE)
University of Copenhagen
Denmark (DK)
Université Fédérale de Toulouse Midi-Pyrénées
France (FR)
How to cite
APA:
Queau, Y., Wu, T., Lauze, F., Durou, J.-D., & Cremers, D. (2017). A non-convex variational approach to photometric stereo under inaccurate lighting. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 (pp. 350-359). Honolulu, HI, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Queau, Yvain, et al. "A non-convex variational approach to photometric stereo under inaccurate lighting." Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA Institute of Electrical and Electronics Engineers Inc., 2017. 350-359.
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