4.6 Article

LieTrICP: An improvement of trimmed iterative closest point algorithm

期刊

NEUROCOMPUTING
卷 140, 期 -, 页码 67-76

出版社

ELSEVIER
DOI: 10.1016/j.neucom.2014.03.035

关键词

Registration; Trimmed iterative closest point; Lie group; Anisotropic scale transformation; LieTrICP

资金

  1. 973 Programme [2011CB 707104]
  2. National Science Foundation of China [61273298, 11101260, 61005002]
  3. First-class Discipline of Universities in Shanghai
  4. Discipline Project at the corresponding level of Shanghai [A.13-0101-12-005]

向作者/读者索取更多资源

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.

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