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

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.

Mots clés: Photometric stereo; registration; shape-from-X

Domaines: Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]

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, ⟨10.1007/978-3-030-75549-2_13⟩. ⟨hal-03172399⟩