Automatic Extraction of the Sparse Prior Correspondences for Non-Rigid Point Cloud Registration  

作　　者：Yan Zhu Lili Tian Fan Ye Gaofeng Sun Xianyong Fang 

机构地区：[1]Department of Sports and Military Education,Anhui University,Hefei,230601,China [2]School of Computer Science and Technology,Anhui University,Hefei,230601,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第8期1835-1856,共22页工程与科学中的计算机建模（英文）

基　　金：supported by Natural Science Foundation of Anhui Province (2108085MF210,1908085MF187);Key Natural Science Fund of Department of Eduction of Anhui Province (KJ2021A0042);Natural Social Science Foundation of China (19BTY091).

摘　　要：Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.

关 键 词：Non-rigid registration point clouds coherent point drift 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]