最邻近曲面约束的近景光学影像与地面激光点云几何配准

doi:10.11947/j.AGCS.2020.20190146

测绘学报 ›› 2020, Vol. 49 ›› Issue (8): 1014-1022.doi: 10.11947/j.AGCS.2020.20190146

最邻近曲面约束的近景光学影像与地面激光点云几何配准

李彩林, 王志勇, 俞路路, 郭宝云

山东理工大学建筑工程学院, 山东淄博 255000

收稿日期:2019-04-22 修回日期:2020-02-20 发布日期:2020-08-25
通讯作者: 王志勇 E-mail:wangzhy1978@163.com
作者简介:李彩林(1985-),男,博士,副教授,研究方向为数字摄影测量与计算机视觉。E-mail:licailin@sdut.edu.cn
基金资助:
国家自然科学基金（41601496；41701525）；山东省重点研发计划项目（2018GGX106002）；山东省自然科学基金资助项目（ZR2017LD002）；山东省艺术科学重点课题（201806353）；山东理工大学齐文化研究专项（2017QWH032）

Geometric registration of close-range optical image and terrestrial laser point cloud constrained by nearest surface

LI Cailin, WANG Zhiyong, YU Lulu, GUO Baoyun

School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255000, China

Received:2019-04-22 Revised:2020-02-20 Published:2020-08-25
Supported by:
The National Natural Science Foundation of China(Nos. 41601496;41701525);The Key Research and Development Program of Shandong Province(No. 2018GGX106002);The Natural Science Foundation of Shandong Province(No. ZR2017LD002);The Key Projects of Shandong Province Arts Science(No. 201806353);The Qi Culture Research Project of Shandong University of Technology(No. 2017QWH032)

摘要/Abstract

摘要： 提出一种以最邻近曲面为约束的近景光学影像与地面激光点云高精度配准方法。根据光学影像生成三维稀疏点云，以影像三维稀疏点邻近的激光点拟合的曲面为约束，结合共线条件方程建立影像三维稀疏点云与三维激光点云间变换模型，通过平差迭代解算实现光学影像与激光点云的高精度几何配准。该方法只需提供初始配准参数，无需对激光点云数据进行特征提取和分割，并且基于曲面约束有效地解决了两个点集之间难以精确确定同名点的问题。通过实际数据试验表明该方法能获得很好的配准精度。

关键词: 最邻近曲面, 光学影像, 激光点云, 几何配准

Abstract: In this paper, a high-precision registration method based on the nearest surface for close-range optical image and terrestrial laser point cloud is proposed.Three-dimensional sparse point cloud is generated from optical images. Constrained by the local surface fitted by the laser points adjacent to the 3D sparse point of the image, a transformation model between the three-dimensional sparse point cloud and the three-dimensional laser point cloud is constructed by using collinear conditional equation. The high precision geometric registration of optical images and the laser point cloud is completed by iterative calculation. The method only needs initial registration parameter and does not need to perform feature extraction and segmentation on the laser point cloud data. In addition, the problem that it is difficult to accurately determine the correspondence points between two sets of points is solved effectively based on the surface constraint. The results of two sets of experimental data show that this method can effectively improve the accuracy of rigid registration algorithm, and can achieve higher registration accuracy.

Key words: nearest surface, optical image, laser point cloud, geometric registration

中图分类号:

P227

李彩林, 王志勇, 俞路路, 郭宝云. 最邻近曲面约束的近景光学影像与地面激光点云几何配准[J]. 测绘学报, 2020, 49(8): 1014-1022.

LI Cailin, WANG Zhiyong, YU Lulu, GUO Baoyun. Geometric registration of close-range optical image and terrestrial laser point cloud constrained by nearest surface[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(8): 1014-1022.

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最邻近曲面约束的近景光学影像与地面激光点云几何配准

Geometric registration of close-range optical image and terrestrial laser point cloud constrained by nearest surface

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