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Surface Reconstruction from Point Clouds
 Jarůšek, Tomáš ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
Surface reconstruction from point clouds represents very modern and widespreadly used method for digitalization of real surfaces. The main focus of this work is on a comparison of several algorithms (Poisson surface reconstruction, Ball Pivoting Algorithm, Fourier surface reconstruction, Wavelet surface reconstruction and Multi-level Partition of Unity implicits) that reconstruct original surface in a form of triangle mesh from an oriented point cloud. Every algorithm was used in a series of tests on both real and synthetic datasets which were also modified to suit more complicated experiments. The following evaluation is done in various  categories. The results are evaluated both visualy and with calculated measures (such as Hausdorff distance). Together these experiments depict a detailed analysis of the state of surface reconstruction algorithms. Our experimets show that the selection of optimal algorithm depends on a  concrete task. Overall Possion surface reconstruction and Fourier surface reconstruction provide the best results.
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