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机载lidar数据对城市建筑的三维模型重建.doc


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分类号密级题目机载 LIDAR 数据对城市建筑的三维模型重建英文题目 The reconstruction of 3D models of city buildings based on air-borne LIDAR data 摘要目前, 众多应用领域对城市建筑物三维模型都有较大的需求。但是,目前城市建筑物的获取效率却较低,为了提高城市建筑物三维重建的效率,本文对现有的建筑物重建方法进行总结,并研究了一种实用的可操作的机载 LIDAR 数据进行建筑物三维重建,获取较为精细的建筑物三维模型。本文在总结和分析了以往从机载 LIDAR 数据中进行城市地区建筑物三维重建的相关技术和理论的基础上,对LIDAR 数据重建建筑物模型的特点,利用点云分割为重建的重要思路,在以往机载 LIDAR 数据进行城市地区建筑物三维重建的理论体系和处理流程的基础上,提出了高精细建筑物三维重建的解决方案,最后通过理论和实验验证了本文解决方案的有效性和可行性。随着城市化进程的加快,城市规划、环境监测和汽车导航等领域对建筑物有了更多的需求,3DGIS 、虚拟现实技术的发展使传统测量方法逐渐暴露出工作效率和精度方面的不足。LIDAR 技术的出现为城市建筑物的快速提取提供了一种新的途径。从LIDAR 点云数据中提取建筑物的边缘,然后采用一种新的三维重建的方法提取出来的建筑物进行重建。本文并没有利用影像相关的信息,仅仅依赖从 LIDAR 数据中提取的几何信息,再结合自上而下的思路来重建建筑物,该方法为大规模快速更新提供了新的思路。目前的研究成果尽管几何信息比较丰富,但是由于没有映射纹理影像,其仿真程度仍有较大的提升空间。关键词:机载 LIDAR ;点云; 建筑物重建 Abstract There are increasing demands in3D models of city buildings in many fields. However, the efficiency of3D building modeling isnot high enough to catch up with the huge demands. This paper present a practical method which fulfill the newly emerging airborne LIDAR data. By this method, bine the new theory and software with regard to the building for a better 3D model of buildings. The paper summarizes and analyzes the past related work. Based on the overview, the problems and ings of existing methods are mastered. Then based on the air-borne LIDAR data, we use a point cloud segmentation as the key ideas for the reconstruction of city buildings. Also, we proposed a set of method for airborne LIDAR data to reconstruct the buildings in urban area. The proposed construction theory is aimed to build high building fa? ade. Finally, we push ona experiment to make the availability ofour process and method. With the accelerated urbanization processing, urban planning, environmental monitoring and the areas of automotive navigation, it has more demand on the building. 3D GIS, virtual reality technology to the traditional measurement have shown up the efficiency and low precision. LIDAR technology provides a new way to extract buildings of cities rapidity. Th

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  • 页数15
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  • 上传人czhenrgjiangh
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  • 时间2016-08-24