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Populating a building Multi Representation Data Base with photogrammetric tools: Recent progress

机译:使用摄影测量工具填充建筑物的多表示形式数据库:最新进展

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More and more frequently, the populating of 3D MRDB's (Multi Representations Data Base) is required to support advanced cartographic applications and advanced geospatial decision analysis. We previously proposed a manual photogrammetric process based on the Multi Representation Acquisition Pattern (MRAP) concept to tackle simultaneously Fine Level Geometries (FLG) extraction and Coarse Level Geometries (CLG) extraction. This paper presents our progress, from an automation standpoint, regarding our approach to populate MRDBs containing building geometries through a photogrammetric multiple representations acquisition process. Two new algorithms dedicated to Multi Representation (MR) acquisition are introduced and constitute two contributions. These combine passive imagery and Digital Surface Model analysis in order to address automation issues. The first algorithm allows for the automatic determination of the MRAP parameters from a single click initialization. The second algorithm aims at supporting part of the MR acquisition when MRAP are not relevant and allows the automatic building footprints extraction. This paper describes the project motivation and its actual progress. It is divided into four parts. The first part concerns the MR data acquisition specifications. A description of the manual prototype is provided and the MRAP concept is described. In the second part, the first algorithm allowing the automatic determination of the MRAP parameters is introduced. The third part is dedicated to the review of the automation performances through the study of three test sites. Finally, our second algorithm, allowing the automatic building footprints extraction is introduced with preliminary results.
机译:为了支持高级制图应用程序和高级地理空间决策分析,越来越需要填充3D MRDB(多表示数据库)。我们先前提出了一种基于多重表示获取模式(MRAP)概念的手动摄影测量过程,以同时处理精细级几何(FLG)提取和粗级几何(CLG)提取。本文从自动化的角度介绍了我们通过摄影测量多表示获取过程填充包含建筑物几何形状的MRDB的方法的进展。引入了两个专用于多表示(MR)采集的新算法,它们构成了两个贡献。这些解决方案将被动图像和数字表面模型分析相结合,以解决自动化问题。第一种算法允许通过单击初始化自动确定MRAP参数。第二种算法旨在在MRAP不相关时支持部分MR采集,并允许自动提取建筑足迹。本文介绍了项目动机及其实际进展。它分为四个部分。第一部分涉及MR数据采集规范。提供了手动原型的描述,并描述了MRAP概念。在第二部分中,介绍了允许自动确定MRAP参数的第一种算法。第三部分致力于通过对三个测试站点的研究来回顾自动化性能。最后,我们介绍了第二种允许自动提取建筑足迹的算法,并提供了初步结果。

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