| 基于匹配点逐层过滤的岩体点云配准方法 |
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| 作者姓名： | 张韬 肖俊 王颖 |
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| 作者单位： | 中国科学院大学人工智能学院, 北京 100049 |
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| 基金项目： | 中国科学院战略性先导科技专项A类(XDA23090304)、中国科学院青年创新促进会优秀会员项目(Y201935)和中央高校基本科研业务费资助 |
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| 摘 要： | 岩体点云配准是岩体三维重建与分析的基础。经典的点云配准方法虽然能够很好地适用于普通点云,但对于岩体点云并不能获得足够的精度。由于岩体点云表面结构复杂,且大部分区域为平面,基于岩体点云的这些特点,提出通过几何特征逐层过滤匹配点的岩体点云配准算法,引入匹配点对的协方差矩阵的特征值和特征向量矩阵,以及曲率、主方向等几何特征逐层过滤匹配点对,精确地找到匹配点对。在不同岩体点云上的实验测试与分析结果表明,该算法在准确度上有明显优势。
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| 关 键 词： | 岩体点云 配准 几何特征 高斯曲率 |
| 收稿时间： | 2020-02-20 |
| 修稿时间： | 2020-04-17 |
Point cloud registration method with layer-by-layer filtering of matching points |
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| Authors: | ZHANG Tao XIAO Jun WANG Ying |
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| Institution: | School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Point cloud registration of rock mass is the basis of rock mass engineering. Although the classic point cloud registration method can be well applied to ordinary point clouds, it can not be used for rock point cloud registration. Due to the complex surface structure of the point cloud of the rock mass, most of the area is flat, based on the characteristics of point cloud of rock mass, this paper proposes a rock mass point cloud registration algorithm that filters matching points layer by layer through geometric features, by introducing the eigenvalues and eigenvector matrices of the covariance matrix of matching point pairs, and geometric features such as curvature and principal direction, the matching point pairs can be accurately found. The experimental test and analysis results on different rock mass point clouds show that the algorithm in this paper has obvious advantages in accuracy. |
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| Keywords: | point cloud of rock mass registration geometric features Gaussian curvature |
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