Automatic registration of partial overlap three-dimensional surfaces
Automatic registration of partial overlap three-dimensional surfaces
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DOI：
10.1109/mace.2010.5535865
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发表时间：
2010-06
期刊：
影响因子：
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通讯作者：
Yong Zhuo;Xiaolei Du
中科院分区：
文献类型：
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作者：
Yong Zhuo;Xiaolei Du
迭代最近点 (ICP) 算法是一种广泛使用的配准三维表面数据的方法。该算法获得的配准质量在很大程度上取决于良好的先前初始估计以及在输入数据集中选择良好的对应点对。如果从数据的无特征区域中选择了太多点，则算法收敛缓慢，发现错误的姿势，甚至发散，特别是在输入点数据集中没有良好的初始对齐的情况下。本文提出了一种用于配准过程的鲁棒点选择策略，该策略基于选择一小组其邻域彼此高度可区分的显着特征点。然后开发基于距离矩阵比较的快速匹配算法来选择最佳对应点集并使两个点集良好对齐。实验证实，所提出的基于显着特征的算法大大降低了匹配过程的复杂度，并且计算时间仅为几秒。
The iterative closest point (ICP) algorithm is a widely used method for registering three-dimensional surface data. The quality of registration obtained by this algorithm depends heavily on a good prior initial estimation and choosing good pairs of corresponding points in the input datasets. If too many points are chosen from featureless regions of the data, the algorithm converges slowly, inds the wrong pose, or even diverges, especially without good initial alignment in the input point datasets. This paper proposed a robust point selection strategy for registration procedure which is based on selecting a small set of salient feature points whose neighborhoods are highly distinguishable from each other. Then a fast matching algorithm is developed based on distance matrix comparisons to select the optimal correspondence point set and bring the two point sets into a good alignment. Experiments confirm that the proposed salient feature-based algorithm is resulting in a great reduction of the complexity of the matching process and the computing time is only a few seconds.