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Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets
Lyon, France June 13-June 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SMI.2007.26IEEE International Conference on Shap ...
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Huaiping Yang, Johannes Kepler University Linz
Bert Juttler, Johannes Kepler University Linz
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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