Teeth Point-clouds 牙齿点云
Point clouds Registratiion 点云拼接
unorganized point-clouds 杂乱点云的
point-clouds 点云
d point clouds 三维点云
2D point clouds 平面点云
Ourmethod has good simplicity as well as good result for most point clouds.
本文提出的算法简单易行,且对多数点云都有较好的效果。
参考来源 - 点云与几何图像的相关研究Registration for point clouds is so important in 3-D object modeling that it is the directly influencing factor to the final synthesis result and model precision.
点云数据配准是三维建模中的关键技术,它直接影响最后的合成结果和模型精度。
参考来源 - 三维激光扫描数据的空间配准研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Following works have been done in the paper: (1) Multi-view point clouds registration.
本文主要进行了以下几方面工作：1、多视点云拼接算法的研究。
The object of post-scanning data processing is to reconstruct surface models from 3D point clouds.
后扫描数据处理的物体将重建来自 3D立体点云的表面的模型。
Firstly, all the pairwise points are searched by taking the curvature of point clouds as the registration relationship.
首先以点云的曲率为联系特征，搜索配准点云的匹配对集合；
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