Isotropic scaling iterative closest point algorithm for partial registration
Isotropic scaling iterative closest point algorithm for partial registration
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DOI：
10.1049/el.2011.1071
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发表时间：
2011-07
影响因子：
1.1
通讯作者：
S. Du;Jihua Zhu;Nanning Zheng;Jihong Zhao;Ce Li
中科院分区：
文献类型：
--
作者：
S. Du;Jihua Zhu;Nanning Zheng;Jihong Zhao;Ce Li
讨论了各向同性尺度点集在包含噪声和缺失数据的离群点情况下的部分配准问题。为了解决这个问题，提出了一种新的基于双向距离的目标函数，通过引入重叠百分比和比例因子。提出了一种新的各向同性尺度迭代最近点（ICP）算法，在每一步迭代中自动计算尺度变换、对应关系和重叠百分比。实验结果表明，该算法比传统的ICP和最先进的算法具有更好的鲁棒性和精确性。
The problem of partial registration of isotropic scaling point sets with outliers including noises and missing data is discussed. To solve this problem, a novel objective function based on bidirectional distance is proposed by introducing an overlapping percentage and a scale factor. Furthermore, a novel isotropic scaling iterative closest point (ICP) algorithm is proposed which can compute the scale transformation, the correspondence and the overlapping percentage automatically at each iterative step. Experimental results demonstrate that the algorithm is more robust and precise than the traditional ICP and the state-of-the-art algorithms.