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基于对象的摄影测量和激光雷达数据集成，用于自动生成复杂的多面体建筑模型。

Object-Based Integration of Photogrammetric and LiDAR Data for Automated Generation of Complex Polyhedral Building Models.

机构信息

Department of Geomatics Engineering, The University of Calgary, 2500 University Drive NW, T2N 1N4, Calgary, Canada; E-Mail:

出版信息

Sensors (Basel). 2009;9(7):5679-701. doi: 10.3390/s90705679. Epub 2009 Jul 15.

DOI:10.3390/s90705679
PMID:22346722
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3274126/
Abstract

This research is concerned with a methodology for automated generation of polyhedral building models for complex structures, whose rooftops are bounded by straight lines. The process starts by utilizing LiDAR data for building hypothesis generation and derivation of individual planar patches constituting building rooftops. Initial boundaries of these patches are then refined through the integration of LiDAR and photogrammetric data and hierarchical processing of the planar patches. Building models for complex structures are finally produced using the refined boundaries. The performance of the developed methodology is evaluated through qualitative and quantitative analysis of the generated building models from real data.

摘要

本研究关注的是为具有直线边界的复杂结构的多面体建筑模型自动生成的方法。该过程首先利用 LiDAR 数据生成建筑物假设，并推导出构成建筑物屋顶的各个平面补丁。然后通过 LiDAR 和摄影测量数据的集成以及平面补丁的分层处理来细化这些补丁的初始边界。最后使用细化后的边界生成复杂结构的建筑物模型。通过对真实数据生成的建筑物模型进行定性和定量分析来评估所开发方法的性能。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4de/3274126/e92085c3fad9/sensors-09-05679f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4de/3274126/489e4d6d98d5/sensors-09-05679f11.jpg
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