Optimal Surface Fitting of Point Clouds Using Local Refinement : Application to GIS Data

Download statistics - Document (COUNTER):

Kermarrec, G.; Skytt, V.; Dokken, T.: Optimal Surface Fitting of Point Clouds Using Local Refinement : Application to GIS Data. Cham : Springer Nature Switzerland AG, 2023 (SpringerBriefs in Earth System Sciences), XIX, 111 S. DOI: https://doi.org/10.1007/978-3-031-16954-0

Repository version

To cite the version in the repository, please use this identifier: https://doi.org/10.15488/13337

Selected time period:

year: 
month: 

Sum total of downloads: 88




Thumbnail
Abstract: 
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.
License of this version: CC BY 4.0 Unported
Document Type: Book
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Mathematik und Physik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 43 48.86%
2 image of flag of United States United States 19 21.59%
3 image of flag of China China 5 5.68%
4 image of flag of Vietnam Vietnam 4 4.55%
5 image of flag of Israel Israel 3 3.41%
6 image of flag of Australia Australia 2 2.27%
7 image of flag of Indonesia Indonesia 1 1.14%
8 image of flag of Hong Kong Hong Kong 1 1.14%
9 image of flag of United Kingdom United Kingdom 1 1.14%
10 image of flag of France France 1 1.14%
    other countries 8 9.09%

Further download figures and rankings:


Hinweis

Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository


Browse