Name
Abstract | ||
|---|---|---|
We propose a robust, feature preserving and user-steerable mesh sampling algorithm, based on the one-to-many mapping of a regular sampling of the Gaussian sphere onto a given manifold surface. Most of the operations are local, and no global information is maintained. For this reason, our algorithm is amenable to a parallel or streaming implementation and is most suitable in situations when it is not possible to hold all the input data in memory at the same time. Using epsilon-nets, we analyze the sampling method and propose solutions to avoid shortcomings inherent to all localized sampling methods. Further, as a byproduct of our sampling algorithm, a shape approximation is produced. Finally, we demonstrate a streaming implementation that handles large meshes with a small memory footprint. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s00371-009-0351-3 | VISUAL COMPUTER |
Keywords | DocType | Volume |
Normal quantization,Surface sampling,Shape approximation,Epsilon-nets | Journal | 25 |
Issue | ISSN | Citations |
5-7 | 0178-2789 | 1 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pablo Diaz-gutierrez | 1 | 51 | 4.54 |
| Jonas Bösch | 2 | 32 | 2.05 |
| Pajarola, Renato | 3 | 1786 | 114.59 |
| Meenakshisundaram Gopi | 4 | 119 | 9.06 |