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  • 标题:SCALE-SPACE EVENTS FOR THE GENERALIZATION OF 3D-BUILDING DATA
  • 本地全文:下载
  • 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
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