Highly Efficient Surface Normal Integration

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Michael Breuß Yvain Quéau Martin Bähr Jean-Denis Durou


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. 

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Breuß, M., Quéau, Y., Bähr, M., & Durou, J. (2016). Highly Efficient Surface Normal Integration. Proceedings Of The Conference Algoritmy, , 204-213. Retrieved from http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/409/326


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