Optimal Surface Fitting of Point Clouds Using Local Refinement: Application to GIS Data (SpringerBriefs in Earth System Sciences)

Optimal Surface Fitting of Point Clouds Using Local Refinement: Application to GIS Data (SpringerBriefs in Earth System Sciences)

Author
Gaël Kermarrec, Vibeke Skytt, Tor Dokken
Publisher
Springer
Language
English
Edition
1st ed. 2023
Year
2022
Page
130
ISBN
3031169530,9783031169533
File Type
pdf
File Size
3.4 MiB

This open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline surface has an overall smooth behavior and allows the modeling of local details with only a limited growth in data volume. In regions where many data points belong to the same smooth area, LR B-splines allow a very lean representation of the shape by locally adapting the resolution of the spline space to the size and local shape variations of the region. The iterative method can be modified to improve the accuracy in particular domains of a point cloud. The use of statistical information criterion can help determining the optimal threshold, the number of iterations to perform as well as some parameters of the underlying mathematical functions (degree of the splines, parameter representation). The resulting surfaces are well suited for analysis and computing secondary information such as contour curves and minimum and maximum points. Also deformation analysis are potential applications of fitting point clouds with LR B-splines.

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