Name
Abstract | ||
|---|---|---|
The most effective and popular tools for obtaining feature aligned quad meshes from triangular input meshes are based on cross field guided parametrization. These methods are incarnations of a conceptual three-step pipeline: (1) cross field computation, (2) field-guided surface parametrization, (3) quad mesh extraction. While in most meshing scenarios the user prescribes a desired target quad size or edge length, this information is typically taken into account from step 2 onwards only, but not in the cross field computation step. This turns into a problem in the presence of small scale geometric or topological features or noise in the input mesh: closely placed singularities are induced in the cross field, which are not properly reproducible by vertices in a quad mesh with the prescribed edge length, causing severe distortions or even failure of the meshing algorithm. We reformulate the construction of cross fields as well as field-guided parametrizations in a scale-aware manner which effectively suppresses densely spaced features and noise of geometric as well as topological kind. Dominant large-scale features are adequately preserved in the output by relying on the unaltered input mesh as the computational domain. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2661229.2661240 | ACM Trans. Graph. |
Keywords | Field | DocType |
computational geometry and object modeling,guiding fields,quad meshing,public records | Quad mesh,Polygon mesh,Parametrization,Computer science,Artificial intelligence,Gravitational singularity,Geometry,Computation,Computer vision,Topology,Public records,Vertex (geometry),Level of detail | Journal |
Volume | Issue | ISSN |
33 | 6 | 0730-0301 |
Citations | PageRank | References |
18 | 0.61 | 39 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hans-Christian Ebke | 1 | 123 | 4.05 |
| Marcel Campen | 2 | 407 | 23.47 |
| David Bommes | 3 | 587 | 27.75 |
| Leif Kobbelt | 4 | 5783 | 333.35 |