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An efficient registration algorithm based on spin image for LiDAR 3D point cloud models
He YQ(何玉庆); Mei YG(梅元刚)
作者部门机器人学研究室
关键词3d Model Registration Spin Image Kd Tree
发表期刊NEUROCOMPUTING
ISSN0925-2312
2015
卷号151期号:1页码:354-363
收录类别SCI ; EI
EI收录号20150700534157
WOS记录号WOS:000347753400041
产权排序1
资助机构National Natural Science Foundation of China [61035005, 61473282]
摘要Spin image is a good point feature descriptor of the 3D surface and has been used in model registration for many applications from medical image processing to cooperation of multiple robots. However, researches show that current Spin-Image based Registration (SIR) algorithms present disadvantages in computational efficiency and robustness. Thus in this paper, aiming at 3D model acquired from LiDAR sensor, a new SIR algorithm is proposed to solve these problems. The new algorithm is on the basis of a new-constructed three-dimensional feature space, which, composed of the curvature, the Tsallis entropy of spin image, and the reflection intensity of laser sensor, is combined with the concept of MD-tree to firstly realize the primary key point matching, i.e., to find the Corresponding Point Candidate Set (CPCS). After that, spin-image based corresponding point searching is conducted with respect to each CPCS to precisely obtain the final corresponding points. The most absorbing advantages of the proposed method are as the following two aspects: on one hand, due to the introduction of the extra features, the fault corresponding relation introduced by spin image based method can be effectively reduced and thus the registration precision and robustness can be improved greatly; on the other hand, the CPCS obtained using low-dimensional feature space and MD-tree reduces extraordinarily the computational burden due to spin-image based correspondence searching. This greatly improves the computational efficiency of the proposed algorithm. Finally, in order to verify the feasibility and validity of the proposed algorithm, experiments are conducted and the results are analyzed. (C) 2014 Elsevier B.V. All rights reserved.
语种英语
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文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/15757
专题机器人学研究室
通讯作者He YQ(何玉庆)
作者单位1.The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning Province, China
2.University of Chinese Academy of Sciences, Beijing, China
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GB/T 7714
He YQ,Mei YG. An efficient registration algorithm based on spin image for LiDAR 3D point cloud models[J]. NEUROCOMPUTING,2015,151(1):354-363.
APA He YQ,&Mei YG.(2015).An efficient registration algorithm based on spin image for LiDAR 3D point cloud models.NEUROCOMPUTING,151(1),354-363.
MLA He YQ,et al."An efficient registration algorithm based on spin image for LiDAR 3D point cloud models".NEUROCOMPUTING 151.1(2015):354-363.
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