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Optimised photometric stereo via non-convex variational minimisation

Hoeltgen, Laurent and Quéau, Yvain and Breuss, Michael and Radow, Georg Optimised photometric stereo via non-convex variational minimisation. (2016) In: 27th British Machine Vision Conference (BMVC 2016), 19 September 2016 - 22 September 2016 (York, United Kingdom).

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Abstract

Estimating the shape and appearance of a three dimensional object from flat images is a challenging research topic that is still actively pursued. Among the various techniques available, Photometric Stereo is known to provide very accurate local shape recovery, in terms of surface normals. In this work, we propose to minimise non-convex variational models for Photometric Stereo that recover the depth information directly. We suggest an approach based on a novel optimisation scheme for non-convex cost functions. Experiments show that our strategy achieves more accurate results than competing approaches.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to University of Cambridge. The definitive version is available at https://www.repository.cam.ac.uk/ The original PDF is available at: http://www.bmva.org/bmvc/2016/papers/paper036/
HAL Id:hal-01445135
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Brandenburgische Technische Universität Cottbus-Senftenberg - BTU (GERMANY)
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Deposited By: IRIT IRIT
Deposited On:10 Jan 2017 09:16

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