Name
Abstract | ||
|---|---|---|
We present a novel algorithm to compute multi-scale curvature fields on triangle meshes. Our algorithm is based on finding robust mean curvatures using the ball neighborhood, where the radius of a ball corresponds to the scale of the features. The essential problem is to find a good radius for each ball to obtain a reliable curvature estimation. We propose an algorithm that finds suitable radii in an automatic way. In particular, our algorithm is applicable to meshes produced by image-based reconstruction systems. These meshes often contain geometric features at various scales, for example if certain regions have been captured in greater detail. We also show how such a multi-scale curvature field can be converted to a density field and used to guide applications like mesh simplification. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Graphics | Topology,Mathematical optimization,Polygon mesh,Curvature,Computer science,Radius,Geometry |
DocType | Volume | Citations |
Journal | abs/1610.07368 | 0 |
PageRank | References | Authors |
0.34 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Seemann | 1 | 2 | 0.70 |
| Simon Fuhrmann | 2 | 157 | 8.62 |
| Stefan Guthe | 3 | 482 | 30.44 |
| Fabian Langguth | 4 | 34 | 2.04 |
| Michael Goesele | 5 | 1006 | 69.58 |