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Building model reconstruction from LIDAR data and aerial photographs.

机译:利用LIDAR数据和航拍照片重建建筑模型。

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摘要

The objective of this research is to reconstruct 3D building models from imagery and LIDAR data. The images used are stereo aerial photographs with known imaging orientation parameters so that 3D ground coordinates can be calculated from conjugate points; and 3D ground objects can be projected to image spaces. To achieve this objective, a method of synthesizing both imagery data and LIDAR data is explored; thus, the advantages of both data sets are utilized to derive 3D building models with a high accuracy. In order to reconstruct complex building models, the polyhedral building model is employed in this research. Correspondingly, the reconstruction method is a data-driven oriented.; The general research procedure can be summarized as: (a) building detection from LIDAR data; (b) 3D building model reconstruction; (c) LIDAR data and imagery data co-registration; and (d) building model refinement. The main role of aerial image data in this research is to improve the geometric accuracy of a building model.; The major contributions of this research lie in four aspects: (1) Two algorithms are developed to perform LIDAR segmentation. Compared with the algorithms proposed by other researchers, these two algorithms work well in urban and suburban areas. In addition, they can keep fine features on the ground; (2) An algorithm of building boundary regularization is proposed in this study. Compared with the commonly used MDL algorithm, it is simple to implement and fast in computation. Longer line segments have larger weights in its adjustment process. This agrees with the fact that longer line segments have more accurate azimuths provided that the accuracy of ending points are the same for all segments; (3) A new method of 3D building model reconstruction from LIDAR data is developed. It is comprised of constructing surface topology, calculating corners from surface intersection, and ordering points of a roof surface in their correct sequence; and (4) A new framework of building model refinement from aerial imagery data is proposed. It refines building models in a consistent approach; and it utilized stereo imagery information and roof constraints in deriving refined building models.
机译:这项研究的目的是从图像和LIDAR数据重建3D建筑模型。使用的图像是具有已知成像方向参数的立体航拍照片,因此可以根据共轭点计算3D地面坐标;可以将3D地面对象投影到图像空间。为了达到这个目的,探索了一种合成图像数据和激光雷达数据的方法。因此,两个数据集的优势都可以用来高精度地推导3D建筑模型。为了重建复杂的建筑模型,本研究采用了多面建筑模型。相应地,重构方法是面向数据驱动的。一般研究程序可以概括为:(a)从LIDAR数据进行建筑物检测; (b)3D建筑模型重建; (c)激光雷达数据和影像数据的共同注册; (d)完善建筑模型。航空图像数据在这项研究中的主要作用是提高建筑模型的几何精度。这项研究的主要贡献在于四个方面:(1)开发了两种算法来进行激光雷达分割。与其他研究人员提出的算法相比,这两种算法在城市和郊区都可以很好地工作。此外,它们可以在地面上保持良好的功能; (2)提出了一种建筑边界正则化算法。与常用的MDL算法相比,它实现简单,计算速度快。较长的线段在其调整过程中具有较大的权重。这与以下事实一致:较长的线段具有更准确的方位角,前提是所有线段的终点精度都相同; (3)提出了一种利用激光雷达数据重建3D建筑模型的新方法。它包括构造表面拓扑,从表面相交处计算角点以及按照正确的顺序排列屋顶表面的顺序点; (4)提出了一种从航空影像数据细化建筑模型的新框架。它以一致的方式完善构建模型;并且利用立体影像信息和屋顶约束来推导精致的建筑模型。

著录项

  • 作者

    Ma, Ruijin.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Geodesy.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大地测量学;遥感技术;
  • 关键词

  • 入库时间 2022-08-17 11:41:28

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