测绘通报 ›› 2017, Vol. 0 ›› Issue (5): 79-81,94.doi: 10.13474/j.cnki.11-2246.2017.0159

• 技术交流 • 上一篇    下一篇

多视激光点云数据融合与三维建模方法研究

宋永存   

  1. 地质出版社, 北京 100083
  • 收稿日期:2017-03-03 修回日期:2017-04-05 出版日期:2017-05-25 发布日期:2017-06-03
  • 作者简介:宋永存(1967-),男,编辑,主要从事三维立体地图的开发、研究及出版工作。E-mail:163syc@163.com

Research on Multi-look Laser Point Cloud Data Fusion and 3D Modeling Method

SONG Yongcun   

  1. Geological Publishing House, Beijing 100083, China
  • Received:2017-03-03 Revised:2017-04-05 Online:2017-05-25 Published:2017-06-03

摘要: 基于特征基元的点云数据配准方法,利用控制点对机载与车载点云数据进行概略匹配,构建了顾及梯度与颜色特征及特征组对的特征点匹配算法模型,根据拟合平面特征解算平移和旋转变换参数,实现了机载与车载点云数据的精确配准,并在此基础上建立了多角度点云数据融合的房屋顶部和立面特征提取、点云数据与光学影像纹理信息匹配的技术流程,实现了建(构)筑物三维精细建模,并通过实例验证了本文所提方法的有效性。

关键词: 多视激光点云, 匹配, 融合, 三维建模

Abstract: Based on the point cloud data registration method of feature primitives, this paper uses the control points to roughly match the airborne and vehicle point cloud data, and constructs the feature point matching algorithm model which takes the gradient and color feature and the feature group pair into account. Then, it realizes the accurate registration of airborne and vehicle point cloud data with translation and rotation transformation parameters obtained by fitting the plane feature. On this basis, the technical process of matching the top and facade features of the multi-angle point cloud data fusion, the point cloud data and the optical image texture information are established, and the building (structure) 3D fine modeling is realized, finally the validity of the proposed method is verified by an example.

Key words: multi-look laser point cloud, matching, fusion, 3D modeling

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