Improved coherent point drift for 3D point clouds registration

Guangrun Xu; Jianmin Huang; Yueni Lu

doi:10.1117/12.2611477

22 October 2021 Improved coherent point drift for 3D point clouds registration

Guangrun Xu, Jianmin Huang, Yueni Lu

Proceedings Volume 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021); 119280D (2021) https://doi.org/10.1117/12.2611477
Event: International Conference on Image Processing and Intelligent Control (IPIC 2021), 2021, Lanzhou, China

Abstract

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.

Citation Download Citation

Guangrun Xu, Jianmin Huang, and Yueni Lu "Improved coherent point drift for 3D point clouds registration", Proc. SPIE 11928, International Conference on Image Processing and Intelligent Control (IPIC 2021), 119280D (22 October 2021); https://doi.org/10.1117/12.2611477

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