LieTrICP: An improvement of trimmed iterative closest point algorithm
LieTrICP: An improvement of trimmed iterative closest point algorithm
复制标题
LieTrICP：修剪迭代最近点算法的改进
DOI：
10.1016/j.neucom.2014.03.035
复制
发表时间：
2014-09-22
期刊：
影响因子：
6
通讯作者：
Hu, Zhiyu
中科院分区：
文献类型：
--
作者：
Dong, Jianmin;Peng, Yaxin;Hu, Zhiyu
我们提出了一个强大的注册方法，两个点集使用李群参数化。我们的算法被称为LieTrICP，因为它结合了修剪迭代最近点（TrICP）算法和李群表示的优点。给定两个低重叠点集，首先求出每个点的对应关系，然后选取重叠点对，利用李群表示估计所选点对的几何变换。这三个步骤迭代进行，以获得最佳的转换。该算法的创新之处有两个：（1）将TrICP推广到各向异性的情况;（2）给出了一个统一的点集配准李群框架，该框架可以扩展到更复杂的变换和高维问题。我们进行了大量的实验，以证明我们的算法是更准确和更强大的比其他几种算法在各种情况下，包括缺失点，扰动和离群值。(C)2014爱思唯尔有限公司版权所有。
We propose a robust registration method for two point sets using Lie group parametrization. Our algorithm is termed as LieTrICP, as it combines the advantages of the Trimmed Iterative Closest Point (TrICP) algorithm and Lie group representation. Given two low overlapped point sets, we first find the correspondence for every point, then select the overlapped point pairs, and use Lie group representation to estimate the geometric transformation from the selected point pairs. These three steps are conducted iteratively to obtain the optimal transformation. The novelties of this algorithm are twofold: (1) it generalizes the TrICP to the anisotropic case; and (2) it gives a unified Lie group framework for point set registration, which can be extended to more complicated transformations and high dimensional problems. We conduct extensive experiments to demonstrate that our algorithm is more accurate and robust than several other algorithms in a variety of situations, including missing points, perturbations and outliers. (C) 2014 Elsevier B.V. All rights reserved.