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Conference papers

Low-rank registration of images captured under unknown, varying lighting

Matthieu Pizenberg 1 Yvain Quéau 1 Abderrahim Elmoataz 1
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : Photometric stereo infers the 3D-shape of a surface from a sequence of images captured under moving lighting and a static camera. However, in real-world scenarios the viewing angle may slightly vary, due to vibrations induced by the camera shutter, or when the camera is hand-held. In this paper, we put forward a low-rank affine registration technique for images captured under unknown, varying lighting. Optimization is carried out using convex relaxation and the alternating direction method of multipliers. The proposed method is shown to significantly improve 3D-reconstruction by photometric stereo on unaligned real-world data, and an open-source implementation is made available.
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Contributor : Yvain Queau <>
Submitted on : Wednesday, March 17, 2021 - 4:46:06 PM
Last modification on : Thursday, April 29, 2021 - 11:04:58 AM


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  • HAL Id : hal-03172399, version 1


Matthieu Pizenberg, Yvain Quéau, Abderrahim Elmoataz. Low-rank registration of images captured under unknown, varying lighting. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2021), 2021, Cabourg, France. pp.153-164. ⟨hal-03172399⟩



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