Small point cloud matching based on bi-direction random KD-tree

机译：基于双向随机KD树的小点云匹配

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The Matching of the point clouds is a key technique in the three-dimensional tracking and 3D reconstruction process, as large amount of feature point data (point cloud) collected from different view-point on an object surface are required. An improved ICP algorithm based on bi-direction random KD tree and camera calibration for small point clouds pair was introduced in the paper. The experiment showed that the registration accuracy could be improved.

机译：点云的匹配是三维跟踪和3D重建过程中的关键技术，因为需要从对象表面的不同视点收集大量的特征点数据（点云）。提出了一种基于双向随机KD树和摄像机标定的改进ICP算法，用于小点云对。实验表明可以提高配准精度。

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来源
《Fifth Asia International Symposium on Mechatronics》|2015年|1-5|共5页
会议地点 Guilin(CN)
作者
F. W. Zhu; S. J. Lv; Z. P. Yuan;
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作者单位

Shanghai University, 200444, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Bi-direction Random KD-tree; Camera Calibration; Matching;

机译：双向随机KD树摄像机标定匹配;

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4. Small point cloud matching based on bi-direction random KD-tree [C] . F. W. Zhu, S. J. Lv, Z. P. Yuan Asia International Symposium on Mechatronics . 2015

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Small point cloud matching based on bi-direction random KD-tree

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