Towards Globally Optimal Normal Orientations for Large Point Clouds
Autor: | Nico Schertler, Stefan Gumhold, Bogdan Savchynskyy |
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Rok vydání: | 2016 |
Předmět: |
Mathematical optimization
Computer science Point cloud 020207 software engineering 02 engineering and technology Energy minimization Computational geometry Computer Graphics and Computer-Aided Design Graph 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Algorithm Surface reconstruction |
Zdroj: | Computer Graphics Forum. 36:197-208 |
ISSN: | 0167-7055 |
Popis: | Various processing algorithms on point set surfaces rely on consistently oriented normals e.g. Poisson surface reconstruction. While several approaches exist for the calculation of normal directions, in most cases, their orientation has to be determined in a subsequent step. This paper generalizes propagation-based approaches by reformulating the task as a graph-based energy minimization problem. By applying global solvers, we can achieve more consistent orientations than simple greedy optimizations. Furthermore, we present a streaming-based framework for orienting large point clouds. This framework orients patches locally and generates a globally consistent patch orientation on a reduced neighbour graph, which achieves similar quality to orienting the full graph. |
Databáze: | OpenAIRE |
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