基于双向距离比的点云配准

Jihua Zhu, Di Wang, Xiuxiu Bai, Huimin Lu, Congcong Jin, Zhongyu Li
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引用次数: 12

摘要

尽管原始的迭代最近点(ICP)算法在配准中得到了广泛的应用,但它无法解决两个点云部分重叠的配准问题。据此,本文提出了一种局部重叠点云的准配方法。给定两个初始构成的云,它首先建立双边对应关系,并计算数据形状中每个点的双向距离。根据双向距离的比值,选择指数函数计算概率值,该概率值可以指示点对是否属于重叠部分。然后,将概率值嵌入到最小二乘函数中进行部分重叠点云的配准,并提出了一种新的ICP算法来获得最优刚体变换。该方法可以在点云重叠率较低的情况下实现较好的配准。在公共数据集上测试的实验结果表明,该方法在鲁棒性方面优于以往的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Registration of Point Clouds Based on the Ratio of Bidirectional Distances
Despite the fact that original Iterative Closest Point(ICP) algorithm has been widely used for registration, itcannot tackle the problem when two point clouds are par-tially overlapping. Accordingly, this paper proposes a ro-bust approach for the registration of partially overlappingpoint clouds. Given two initially posed clouds, it firstlybuilds up bilateral correspondence and computes bidirec-tional distances for each point in the data shape. Based onthe ratio of bidirectional distances, the exponential functionis selected and utilized to calculate the probability value,which can indicate whether the point pair belongs to theoverlapping part or not. Subsequently, the probability val-ue can be embedded into the least square function for reg-istration of partially overlapping point clouds and a novelvariant of ICP algorithm is presented to obtain the optimalrigid transformation. The proposed approach can achievegood registration of point clouds, even when their overlappercentage is low. Experimental results tested on public da-ta sets illustrate its superiority over previous approaches onrobustness.
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