Improved coherent point drift for 3D point clouds registration

被引:0
|
作者
Xu, Guangrun [1 ]
Huang, Jianmin [1 ]
Lu, Yueni [1 ]
机构
[1] Guangxi Normal Univ, Coll Comp Sci & Engn, Guilin, Guangxi, Peoples R China
关键词
Improved coherent point drift; Gaussian lattice filtering; global square iteration method; outlier optimization; point cloud registration;
D O I
10.1117/12.2611477
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Coherent Point Drift (CPD) is one of the popular robust point cloud registration algorithms in recent years. However, the algorithm uses fast Gaussian transformation to calculate the matrix-vector product, resulting in slower overall registration efficiency. We propose an improved coherent point drift (ICPD) algorithm, which introduces faster Gaussian lattice filtering to calculate the above product and uses the global squared iterative method to reduce the number of iterations of the CPD algorithm. In addition, the outlier w is not accurately expressed in CPD. We propose an iterative outlier formula to solve this problem. Experiments show that the improved algorithm is about two orders of magnitude faster than the CPD algorithm, 1-2 times faster than the ICP algorithm, and shows superior performance in environments with different noise and outlier distributions.
引用
收藏
页数:7
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