The Improvement of Iterative Closest Point with Edges of Projected Image

被引:0
|
作者
Wang C. [1 ]
机构
[1] School of Information and Communication Engineering, University of Electronic Science and Technology of China
来源
关键词
Iterative Closest Point; Point cloud; Registration;
D O I
10.1016/j.vrih.2022.09.001
中图分类号
学科分类号
摘要
Background: There are many regular-shape objects in the artificial environment. It is difficult to distinguish the poses of these objects, when only geometric information is utilized. With the development of sensor technologies, we can utilize other information to solve this problem. Methods: We propose an algorithm to register point clouds by integrating color information. The key idea of the algorithm is that we jointly optimize dense term and edge term. The dense term is built similarly to iterative closest point algorithm. In order to build the edge term, we extract the edges of the images obtained by projecting the point clouds. The edge term prevents the point clouds from sliding in registration. We utilize this loosely coupled method to fuse geometric and color information. Results: The experiments demonstrate that edge image approach improves the precision and the algorithm is robust. © 2022 Beijing Zhongke Journal Publishing Co. Ltd
引用
收藏
页码:279 / 291
页数:12
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