Highly Efficient Surface Normal Integration

Michael Breuss (1) , Yvain Quéau (2) , Martin Bähr (1) , Jean-Denis Durou (2)

1 BTU - Brandenburg University of Technology [Cottbus – Senftenberg]
2 IRIT-REVA - Real Expression Artificial Life

The integration of surface normals for the computation of a surface in 3D space is a classic problem in computer vision. However, even nowadays it is still a challenging task to device a method that combines the flexibility to deal with non-trivial computational domains with high accuracy, robustness and computational efficiency. In this paper we propose to use for the first time in the literature Krylov subspace solvers as a main step in tackling the task. While these methods can be very efficient, they may only show their full potential when combined with a numerical preconditioning and even more importantly, a suitable initialization. To address the latter issue we propose to compute this initial state via a recently developed fast marching integrator. Numerical experiments prove the benefits of this novel combination.

Mots clés: Krylov subspace methods; Poisson integration; Surface normal integration; Fast marching methods

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]; Traitement du signal et de l'image [eess.SP]; Traitement des images [eess.IV]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Intelligence artificielle [cs.AI]

Michael Breuss, Yvain Quéau, Martin Bähr, Jean-Denis Durou. Highly Efficient Surface Normal Integration. Conference Algoritmy 2016 (ALGORITMY 2016), Mar 2016, Podbanskè, Slovakia. pp. 204-213. ⟨hal-01535947⟩