TREE POINT CLOUDS REGISTRATION USING AN IMPROVED ICP ALGORITHM BASED ON KD-TREE

被引：30

作者：

Li, Shihua ^{[1
]}

Wang, Jingxian ^{[1
]}

Liang, Zuqin ^{[1
]}

Su, Lian ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Resources & Environm, West Hitech Zone, 2006 Xiyuan Ave, Chengdu 611731, Peoples R China

来源：

2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2016年

基金：

中国国家自然科学基金;

关键词：

LiDAR; point cloud data; registration; Iterative Closest Point (ICP); k-d tree; LIDAR DATA;

D O I：

10.1109/IGARSS.2016.7730186

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The light detection and ranging (LiDAR) technology plays an important role in obtaining the three-dimensional information. A large number of point cloud data of the objects can be obtained through the LiDAR technology. The Iterative Closest Point (ICP) algorithm was widely used for registering the point cloud data, which typically only scan an object from one direction at a time. However, massive point cloud data has brought a great number of troubles to this registration method. The k-d tree is similar to the general tree structure and it can store, manage and search data efficiently. Therefore, an improved ICP algorithm which based on k-d tree was presented for tree point cloud data registration in this paper. The results showed that the improved ICP algorithm can improve the speed of registration about 10 times higher, and it also has obvious advantages in accuracy of registration.

引用

页码：4545 / 4548

页数：4

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