| Autor: |
Hao Liu, Martin Huska, Yuchen He, Sung Ha Kang |
| Přispěvatelé: |
Springer, Yuchen He, Martin Huska, Sung Ha Kang, and Hao Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Springer Proceedings in Mathematics & Statistics ISBN: 9789811627002 |
| Popis: |
We consider constructing a surface from a given set of point cloud data. We explore two fast algorithms to minimize the weighted minimum surface energy in [Zhao, Osher, Merriman and Kang, Comp.Vision and Image Under., 80(3):295-319, 2000]. An approach using Semi-Implicit Method (SIM) improves the computational efficiency through relaxation on the time-step constraint. An approach based on Augmented Lagrangian Method (ALM) reduces the run-time via an Alternating Direction Method of Multipliers-type algorithm, where each sub-problem is solved efficiently. We analyze the effects of the parameters on the level-set evolution and explore the connection between these two approaches. We present numerical examples to validate our algorithms in terms of their accuracy and efficiency. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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