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Titlebook: Optimal Surface Fitting of Point Clouds Using Local Refinement; Application to GIS D Ga?l Kermarrec,Vibeke Skytt,Tor Dokken Book‘‘‘‘‘‘‘‘ 20

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書(shū)目名稱(chēng)Optimal Surface Fitting of Point Clouds Using Local Refinement
副標(biāo)題Application to GIS D
編輯Ga?l Kermarrec,Vibeke Skytt,Tor Dokken
視頻videohttp://file.papertrans.cn/703/702934/702934.mp4
概述This book is open access, which means that you have free and unlimited access.Provides a comprehensive description of an innovative surface approximation method for large data set.Shows a new procedur
叢書(shū)名稱(chēng)SpringerBriefs in Earth System Sciences
圖書(shū)封面Titlebook: Optimal Surface Fitting of Point Clouds Using Local Refinement; Application to GIS D Ga?l Kermarrec,Vibeke Skytt,Tor Dokken Book‘‘‘‘‘‘‘‘ 20
描述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 fittin
出版日期Book‘‘‘‘‘‘‘‘ 2023
關(guān)鍵詞Open Access; Surface Modeling; Optimum Point Cloud Approximation; Akaike Information Criterion; LR B-Spl
版次1
doihttps://doi.org/10.1007/978-3-031-16954-0
isbn_softcover978-3-031-16953-3
isbn_ebook978-3-031-16954-0Series ISSN 2191-589X Series E-ISSN 2191-5903
issn_series 2191-589X
copyrightThe Author(s) 2023
The information of publication is updating

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LR B-Splines for Representation of Terrain and Seabed: Data Fusion, Outliers, and Voids,arying data density, (ii) outliers should be eliminated without deleting features, (iii) voids, also called holes, or data gaps should be treated specifically to avoid the drop of the approximated surface in domains without points. These factors tend to be even more challenging when point clouds acq
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