@inproceedings{BreussQueauBaehretal., author = {Breuß, Michael and Qu{\`e}au, Yvain and B{\"a}hr, Martin and Durou, Jean-Denis}, title = {Highly Efficient Surface Normal Integration}, series = {Proceedings of the Conference Algoritmy 2016, 20th Conference on Scientific Computing, Vysok{\´e} Tatry - Podbansk{\´e}, Slovakia, March 14 - 18}, booktitle = {Proceedings of the Conference Algoritmy 2016, 20th Conference on Scientific Computing, Vysok{\´e} Tatry - Podbansk{\´e}, Slovakia, March 14 - 18}, publisher = {Publishing House of Slovak University of Technology in Bratislava}, address = {Bratislava}, isbn = {978-80-227-4544-4}, pages = {204 -- 213}, language = {en} } @misc{BaehrBreussQueauetal., author = {B{\"a}hr, Martin and Breuß, Michael and Qu{\`e}au, Yvain and Sharifi Boroujerdi, Ali and Durou, Jean-Denis}, title = {Fast and accurate surface normal integration on non-rectangular domains}, series = {Computational Visual Media}, volume = {3}, journal = {Computational Visual Media}, number = {2}, issn = {2096-0433}, doi = {10.1007/s41095-016-0075-z}, pages = {107 -- 129}, abstract = {The integration of surface normals for the purpose of computing the shape of a surface in 3D space is a classic problem in computer vision. However, even nowadays it is still a challenging task to devise a method that is flexible enough to work on non-trivial computational domains with high accuracy, robustness, and computational efficiency. By uniting a classic approach for surface normal integration with modern computational techniques, we construct a solver that fulfils these requirements. Building upon the Poisson integration model, we use an iterative Krylov subspace solver as a core step in tackling the task. While such a method can be very efficient, it may only show its full potential when combined with suitable numerical preconditioning and problem-specific initialisation. We perform a thorough numerical study in order to identify an appropriate preconditioner for this purpose. To provide suitable initialisation, we compute this initial state using a recently developed fast marching integrator. Detailed numerical experiments illustrate the benefits of this novel combination. In addition, we show on real-world photometric stereo datasets that the developed numerical framework is flexible enough to tackle modern computer vision applications.}, language = {en} }