Incremental Solid Modeling from Sparse Structure-from-Motion Data with Improved Visual Artifacts Removal

Abstract : In the recent years, a family of 2-manifold surface reconstruction methods from a sparse Structure-from-Motion points cloud based on 3D Delaunay triangulation was developed. This family consists of batch and incremental variations which include a step that remove visual artifacts. Although been necessary in the term of surface quality, this step is slow compared to the other parts of the algorithm and is not well suited to be used in an incremental manner. In this paper, we present two other methods for removing visual artifacts. They are evaluated and compared to the previous one in the incremental context where the need of new methods is the highest. Taken separately, they provide medium results, but used together they are as good as the old method in the terms of surface quality, and at the same time, processing time is almost three times smaller.
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Communication dans un congrès
IAPR International Conference on Pattern Recognition, Aug 2014, Stockholm, Sweden
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Vadim Litvinov, Maxime Lhuillier. Incremental Solid Modeling from Sparse Structure-from-Motion Data with Improved Visual Artifacts Removal. IAPR International Conference on Pattern Recognition, Aug 2014, Stockholm, Sweden. 〈hal-01635432〉

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