Point Cloud Registration Algorithm Based on Probability Iterative Closest Point
ZHAO Fuqun
ZHOU Mingquan
WANG Jing
Abstract：Aiming at the failure registration of iterative closest point (ICP) algorithm brought by noise, the paper proposes a point cloud registration algorithm with noise based on Expectation Maximum (EM) estimation, which is named probability iterative closest point (PICP) algorithm.Firstly, a point-to-point correspondence is built between two point clouds, thus the registration accuracy is improved greatly.Then, Gaussian model is introduced into ICP algorithm, the singular value decomposition (SVD) method is used to solve the problem of rigid body transformation, thus the accurate registration of two point clouds is completed.The experimental results show that PICP algorithm not only can complete point clouds registration with noise of the same object from different angles rapidly and accurately, but also can achieve complete matching and partial matching of fracture surfaces between rigid body blocks effectively.It is an accurate and fast algorithm which can effectively avoid noise and external interference.It has more extensive application scopes.
Keywords：point cloud registrationiterative closest pointGaussian modelprobabilitynoise
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 419-422,522 )