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基于等高线簇分析的复杂建筑物模型重建方法
Contour Clustering Analysis for Building Reconstruction from LIDAR Data

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文摘 近年来,基于LIDAR点云数据的建筑物重建模型一直是研究的热点.目前,出现的许多算法对简单建筑物,如平顶房屋,人字行屋顶及其他规则房屋的重建取得了不错的效果,但是,对于结构复杂的建筑物重建问题仍然有待解决.针对这一问题,本文提出了一种利用等高线簇分析从LIDAR数据中自动重建复杂建筑物模型的新算法.该算法是一种自底向上的数据驱动方法,以等高线所反映出的建筑物轮廓特征为基础,充分利用等高线封闭性和明确的拓扑关系,采用等高线形状分析的方法来实现建筑物的检测和模型识别与重建.算法实现分为4个步骤,首先,通过对LIDAR点云数据的DELAUNAY三角化跟踪提取等高线,然后利用等高线的长度,面积等形状参数来提取建筑物等高线,再通过拓扑分析,以及形状匹配的方法对等高线进行分簇,得到同一建筑物不同组成部分的等高线簇,最后,对各簇等高线进行模型参数优化并按拓扑关系进行重组得到完整的建筑物模型.通过对多层次,多曲面等复杂建筑物的重建实验证明了此方法的可行性
其他语种文摘 The automatic building reconstruction from LIDAR data has been a hot issue for several years. Many methods and algorithms have been put forward to reconstruct the models of simple buildings, such as of flat roof, gable roof,or other rectangular shape. But it remains an open problem for the reconstruction of complex buildings. In this paper,a new idea is introduced to process the complex buildings. It is based on the contour clustering analysis of LADAR data and a bottom-up method using data-driven processing. Contours contain the shape information of object boundary, and they are closed, complete, and having explicit topological relationships among each other. So we can use these valuable characters to guide the building reconstruction. In this paper,a concept of contours cluster is introduced, which is based on the following observations: the contours of a building are usually very similar to each other in every part of the building;the nested similar contours are defined as a cluster of similar contour. The contour cluster reflects the detailed feature of the corresponding object. Analyzing the shape differences among contours clustering, the different parts of the whole complex building can be found out. So we can say, contour clustering is very useful, and is the core of the method. The process includes 4 main steps. Firstly, the LIDAR point is pre-processed, and the Delaunay mesh is constructed with the processed LIDAR points and the initial contours are traced. Secondly, some shape features are used to distinguish the contours on buildings or on other objects. With thresholds of contour length and area, some contours of vegetation can be removed. Thirdly the topology relationship and similarity relationship between contours are analyzed. Based on these relations, the contours are clustered to form the parts of buildings. At last, the building model of different types can be reconstructed from the clusters of contours. To test the approach presented above,2 experiment data with representative building models are applied. The results show our method has following advantages:(1) the closeness of contours can effectively avoid the difficulty of edges grouping in conventional reconstruction methods;(2) using contour cluster analysis can extract different hierarchical structures of the complex building;and(3) even curved surface buildings can be correctly constructed using our method
来源 地球信息科学学报 ,2010,12(5):641-648 【扩展库】
关键词 LIDAR ; 等高线 ; 分簇 ; 形状匹配
地址

武汉大学, 测绘遥感信息工程国家重点实验室, 武汉, 430079

语种 中文
文献类型 研究性论文
ISSN 1560-8999
学科 自然地理学
基金 国家自然科学基金 ;  国家863计划
文献收藏号 CSCD:4100220

参考文献 共 20 共1页

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引证文献 4 篇

1 徐宏根 面向对象的植被与建筑物重叠区域的点云分类方法 国土资源遥感,2012(2):23-27
CSCD被引 4 次

2 何美章 从灾后机载激光点云自动检测损毁房屋的等高线簇分析方法 测绘学报,2015,44(4):407-413
CSCD被引 4 次

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