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摘要: 三维激光扫描点云在建筑物场景配准中存在同名特征难以区分、投票匹配算法复杂度高等问题。为此，提出了一种基于平面基元组的建筑物场景点云自动配准方法。平面基元组被定义为具有近似相同法向量的点云面集合。该方法从点云中提取平面基元，根据平面法向量方向，划分平面基元组，然后借助基元组搜索同名平面，利用单位四元数法估计转换参数。实验结果表明，该方法适用于建筑物场景，能够实现点云的自动配准。Abstract: In this paper, we present an automatic registration method based on planar primitive groups for building point clouds. This method distinguishes planar features with similar structures found in urban scenes, and reduces feature matching search complexity. In the method, planar patches with similar normal vectors are defined as a planar primitive group. We extract planes from point clouds as planar primitives. Using a threshold, we cluster the planar primitives with the similar normal vectors into groups. Finally, we match the planar primitives in groups, and calculate transformation parameters with an extended quaternion method. Experimental results show that this method is effective for automatic registration of building point clouds.
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Keywords:
- building /
- plane extraction /
- hierarchical clustering /
- planar primitive group /
- point clouds registration /
- RANSAC
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图 1 利用层次聚类对平面基元分组示意图
Figure 1. Schematic Diagram of Planar Primitives Grouping Using Hierarchical Cluster
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图 2 与目标平面基元组对应的参考平面基元组搜索过程
Figure 2. Searching the Reference Primtive Groups Corresponding to Object Primitive Groups
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图 4 平面基元几何中心矢量约束
Figure 4. Constraint with Vectors from Reference to Target Planar Primitive Centers
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