应用科学学报 ›› 2017, Vol. 35 ›› Issue (2): 217-225.doi: 10.3969/j.issn.0255-8297.2017.02.008

• 信号与信息处理 • 上一篇    下一篇

点云数据稀疏区域建筑物立面重建方法

刘亚文1, 覃苏舜1,2   

  1. 1. 武汉大学 遥感信息工程学院, 武汉 430079;
    2. 广西壮族自治区测绘地理信息局, 南宁 530023
  • 收稿日期:2016-05-06 修回日期:2016-06-08 出版日期:2017-03-30 发布日期:2017-03-30
  • 作者简介:刘亚文,教授,研究方向:数字摄影测量、多源数据三维重建,E-mail:liuyawen70@126.com
  • 基金资助:

    中央高校基本科研业务费专项基金(No.2042014kf0294)资助

Building Facade Reconstruction on Sparse LiDAR Data Region

LIU Ya-wen1, QIN Su-shun1,2   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
    2. Guangxi Bureau of Surveying, Mapping and Geoinformation, Nanning 530023, China
  • Received:2016-05-06 Revised:2016-06-08 Online:2017-03-30 Published:2017-03-30

摘要:

建筑物立面兼顾规则和非规则的几何结构排列,利用先验或提取的立面结构规则推理数据稀疏区域立面模型时,会产生不合理的重建结果.为此,提出一种结合规则推理和点云数据验证的数据稀疏区域建筑物立面重建方法,能够对推测的立面模型合理性进行验证.在利用影像数据改善立面点云数据初始重建模型偏移的基础上,分析立面结构的排列规律.采用四邻域模板匹配方法推理点云数据稀疏区域立面几何结构的位置和类型.最后用点云数据验证推理重建结果的可靠性.实验表明,对于结构多样的建筑物立面,该方法可检测出不合理的重建结果,提高了基于规则建筑物立面重建的可靠性.

关键词: 建筑物立面重建, 规则推理, 点云数据稀疏, 点云数据验证

Abstract:

A building facade is composed of regular and irregular geometric structures. When the prior or extracted rules of facade structure are used to reconstruct the sparse data area, unreasonable reconstructed geometric structures will appear. This paper presents a method for building façade reconstruction on LiDAR data sparse region by combining rule inference and laser data verification. Building facade reconstruction is first introduced, including initial model reconstruction from LiDAR data and refinement combining LiDAR data and images. The reconstruction method is discussed for data sparse region with a focus based on an analysis of façade regularity, prediction of missing geometry structures and verification with point cloud data. Experiments show that the method can effectively detect unreasonable reconstruction and improve reliability of facade reconstruction based on the data sparse region.

Key words: sparse point data, building facade reconstruction, rule inference, point data verification

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