基于线对间法向距离特征的机载和车载点云配准算法
Airborne and Vehicle-borne LiDAR Point Cloud Registration Algorithm Based on the Normal Distance Feature between Line Pairs
陈淋 1张同刚 2王鑫 1李文君 2陈婷婷 2炊宇恒 2熊鑫2
作者信息
- 1. 四川省冶金地质勘查局测绘工程大队,四川 成都 610000
- 2. 西南交通大学 地球科学与环境工程学院,四川 成都 611756
- 折叠
摘要
针对线对长度不一致引起的转换参数不准确问题,提出了基于线对间法向距离特征的异源点云配准算法.该算法以线段间豪斯多夫距离为相似性测度筛选同名线对,并按照线对索引出现次数去除一对多情况等有歧义的同名线对,在不等长线对存在时引入线对间法向距离特征联合构建配准模型解决线对不等长存在时的配准问题.实测数据表明,存在线对不等长的情况下,该算法配准后的平面距离偏差为 15.6 mm,可以实现机载和车载点云的配准.
Abstract
Aiming at the problem of inaccurate transformation parameters caused by inconsistent line pair lengths,this paper proposes a heterogenous point cloud registration algorithm based on the normal distance feature between line pairs.The algorithm screens corre-sponding line pairs by taking the Hausdorf distance between line segments as the similarity measure,removes ambiguous corresponding line pairs such as one-to-many cases according to the number of occurrence of the line pair indexes,and introduces the normal dis-tance feature between line pairs to jointly construct registration model to solve the registration problem when the unequal lenth line pair exists.The measured data show that in the case of unequal length of line pairs,the planimetric distance deviation after registration of this algorithm is 15.6 mm,which can realize the registration of airborne and vehicle-borne point clouds.
关键词
异源点云配准/线特征/端点不匹配/长度不一致Key words
heterogenous point cloud registration/line features/endpoint mismatches/inconsistent pair lengths引用本文复制引用
出版年
2024
NETL
NSTL
万方数据