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IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07)
Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets
Lyon, France
June 13-June 15
ISBN: 0-7695-2815-5
| ASCII Text | x | ||
| Huaiping Yang, Bert Juttler, "Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets," Shape Modeling and Applications, International Conference on, pp. 251-260, IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07), 2007. | |||
| BibTex | x | ||
| @article{ 10.1109/SMI.2007.26, author = {Huaiping Yang and Bert Juttler}, title = {Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets}, journal ={Shape Modeling and Applications, International Conference on}, volume = {0}, year = {2007}, isbn = {0-7695-2815-5}, pages = {251-260}, doi = {http://doi.ieeecomputersociety.org/10.1109/SMI.2007.26}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Shape Modeling and Applications, International Conference on TI - Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets SN - 0-7695-2815-5 SP251 EP260 A1 - Huaiping Yang, A1 - Bert Juttler, PY - 2007 KW - mesh reconstruction KW - point cloud KW - displacement maps KW - T-spline KW - level sets VL - 0 JA - Shape Modeling and Applications, International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SMI.2007.26
We propose a new method for constructing a piecewise smooth mesh from a set of unorganized data points, which may be non-uniformly sampled, noisy, and even containing holes. The method is based on the construction of an implicit representation of the surface, by using smooth (C2 in our case) T-spline scalar functions. We first generate the Tspline control grid, and use an evolution process such that the resulting T-spline level sets capture the topology and outline of the object to be reconstructed. The initial mesh with high quality is obtained from the implicit T-spline function through the marching triangulation method. Then we project each data point to the initial mesh, and get a scalar displacement field. Detailed features will be captured by the displaced mesh. We also propose an additional evolution process, which combines data-driven velocities and featurepreserving bilateral filters, in order to reproduce sharp features.
Index Terms:
mesh reconstruction, point cloud, displacement maps, T-spline, level sets
Citation:
Huaiping Yang, Bert Juttler, "Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets," smi, pp.251-260, IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07), 2007
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