测绘通报 ›› 2023, Vol. 0 ›› Issue (8): 126-129.doi: 10.13474/j.cnki.11-2246.2023.0244

• 技术交流 • 上一篇    下一篇

三维激光扫描仪在建筑物精细重建中的应用

李捷斌1,2, 王宁1,2, 赵春晨1,2   

  1. 1. 陕西工业职业技术学院, 陕西 咸阳 712000;
    2. 咸阳市数字城市与地理空间大数据技术重点实验室, 陕西 咸阳 712000
  • 收稿日期:2023-05-09 发布日期:2023-09-01
  • 作者简介:李捷斌(1981-),男,硕士,副教授,主要研究方向为激光点云数据融合处理。E-mail:522166421@qq.com
  • 基金资助:
    陕西工业职业技术学院校级自然科学重点项目(2022YKZD-004);高校地下管网智能化监测系统研究与应用;陕西工业职业技术学院青年科技创新团队(KCTD2002-01);智慧城市空间信息技术研究与应用创新团队;陕西省教育厅2020年度一般专项科学研究计划(20JK0501)关中中心城市滑坡隐患区三维模拟分析及评估防护研究

3D laser scanner in buildings application in fine reconstruction

LI Jiebin1,2, WANG Ning1,2, ZHAO Chunchen1,2   

  1. 1. Shaanxi Polytechnic Institute, Xianyang 712000, China;
    2. Xianyang Key Laboratory of Digital City and Geospatial Big Data Technology, Xianyang 712000, China
  • Received:2023-05-09 Published:2023-09-01

摘要: 数字城市建设的不断推进和三维数据采集技术的发展,对城市中重点地区建筑模型的精细程度提出了更高的要求。目前在大规模城市三维建模中,地面激光扫描与倾斜摄影测量联合建模的方法因其建模效率高被广泛应用。但其模型精细程度不能满足重点地区建筑物建模精细度的要求,因此采用多源点云融合进行小区域高精度的三维建模。融合建模虽然模型精细度较高,但前期点云数据处理工作量较大,影响建模效率。本文提出一种建筑物精细建模的方法,并通过实际数据进行验证对比。结果表明,该方法在实现建筑物精细建模的同时,提高了密集点云的自动化处理程度和建模效率。

关键词: 三维激光扫描, 点云融合, 建筑物精细建模

Abstract: With the continuous promotion of digital city construction and the development of 3D data acquisition technology, the precision of architectural model in key areas of cities has put forward higher requirements. At present, in large-scale urban 3D modeling, the method of ground laser scanning and tilt photogrammetry combined modeling is widely used because of its high modeling efficiency, but its model precision can not meet the requirements of building modeling precision in key areas. Therefore, multi-source point cloud fusion modeling is adopted for small-scale high-precision 3D modeling. Although fusion modeling has a relatively high level of model precision, the workload of point cloud data processing in the early stage is significant, which affects modeling efficiency. This article proposes a method for fine modeling of buildings and compares it with actual data. This method not only achieves fine modeling of buildings, but also improves the automation of dense point clouds and improves modeling efficiency.

Key words: 3D laser scanning, point cloud fusion, fine building modeling

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