电子科技大学学报2026，Vol.55Issue(2)：201-214,14.DOI:10.12178/1001-0548.2024282
基于区间分割和兼容加权的点云配准算法
Point cloud registration algorithm based on interval segmentation and compatibility weighting
摘要
Abstract
Aiming at the problem of low registration accuracy of point clouds with small overlapping areas and few shared feature points,a point cloud registration algorithm based on interval segmentation and compatible weighting is proposed.In this algorithm,the point cloud is divided into several sub-intervals by distance segmentation,and the histogram similarity is obtained by constructing the feature descriptors of the sub-intervals,so as to determine the corresponding relationship of the sub-intervals.By introducing credibility and consistency constraints,the combination coefficients of rigid body transformation are solved,and the global registration is obtained from local registration,thereby achieving the coarse registration of point cloud.Finally,two-point sampling is carried out based on the scale invariant compatibility constraint,the compatibility weight matrix of corresponding point pairs is calculated,the rigid body transformation with maximum consensus is obtained after voting,and the fine registration of point cloud is completed.Stanford point cloud data model,3DMatch indoor scene data model and the farmland point cloud data model are used to verify the experiment.The results show that compared with the six registration algorithms,the proposed algorithm has the highest registration accuracy and the lowest registration time consumption.In the registration of Stanford point cloud data,the average accuracy of the proposed algorithm is improved by more than 10%,and the average time consumption is reduced by more than 14%.In the point cloud registration of indoor scenes,the average accuracy of the proposed algorithm is improved by more than 20%,and the average time consumption is reduced by more than 14%.In the registration of farmland point cloud data,the proposed algorithm has increased the average accuracy by more than 21%and reduced the average time consumption by more than 16%.Therefore,it can be said that the point cloud registration algorithm b ased on interval segmentation and compatible weighting is an efficient point cloud registration algorithm.关键词
点云配准/区间分割/组合系数/兼容性权重矩阵/共识最大化Key words
point cloud registration/interval segmentation/combination coefficient/compatibility weight matrix/consensus maximization分类
信息技术与安全科学引用本文复制引用
赵夫群,黄鹤,耿国华..基于区间分割和兼容加权的点云配准算法[J].电子科技大学学报,2026,55(2):201-214,14.基金项目
国家自然科学基金(62271393) （62271393）
陕西省教育厅科学研究计划项目(25JS049) （25JS049）
