文章基本信息

标题：SCALE-SPACE EVENTS FOR THE GENERALIZATION OF 3D-BUILDING DATA
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作者：Helmut Mayer
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2000
卷号：XXXIII Part B4 (/1-3)
页码：639-646
出版社：Copernicus Publications
摘要：In this paper we aim at generalizing, i.e., simplifying, 3D building data automatically employing vector-based morphology and discrete/continuous curvature space. So-called " scale-space events" , for which the link to the semantics of objects has been shown, play a major role for the simplification. The simplified data can be used to build up a level of detail (LOD) structure making the visualization of large data sets feasible by visualizing objects at a larger distance from the viewer based on a less detailed representation. Another point of view on our approach is that we base model-generalization from cartography which transforms data to the right level of abstraction for a particular analysis task on the formally well-defined theory of scale-spaces. Results for an implementation of the approach based on the computational geometry algorithm library (CGAL) public domain library show the validity of the approach
关键词：Generalization; scale-space; abstraction; level of detail