Surface Reconstruction and Fitting from Dense Point Sets

@inproceedings{TertoisRM2005a,
 abstract = { During seismic interpretation, large numbers of surfaces often have to be reconstructed, for instance when building sets of faults. This can become a tedious task when the point sets are dense, which slows down surface fitting operations. The algorithm introduced in this paper offers a fast way of reconstructing complex surfaces from dense point sets. First, a planar surface is created from the convex hull of the point set. Then the distance between the points and the surface is computed and smoothly interpolated on the surface. This distance is used to fit the surface to the points. An additional step can be performed to extract a family of non-convex borders from the point set and the surface. Using these borders as input, the algorithm can create fitted surfaces with non-convex borders, which closely fit the points. However, multi-valued surfaces cannot be reconstructed using this algorithm. This method is based on the matrix Discrete Smooth Interpolation (DSI), which guarantees convergence in a reasonable time. This matrix DSI allows the algorithm to take large numbers of points into account and still to run quickly. Depending on the origin of the data, two different styles of fitting create horizon-like surfaces or fault-like surfaces. },
 author = { Tertois, Anne-Laure AND Mallet, Jean-Laurent },
 booktitle = { 25th gOcad Meeting },
 month = { "june" },
 publisher = { ASGA },
 title = { Surface Reconstruction and Fitting from Dense Point Sets },
 year = { 2005 }
}