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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)
Department机器人学研究室
Source PublicationNEUROCOMPUTING
ISSN0925-2312
2015
Volume151Issue:1Pages:354-363
Indexed BySCI ; EI
EI Accession number20150700534157
WOS IDWOS:000347753400041
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China [61035005, 61473282]
Keyword3d Model Registration Spin Image Kd Tree
AbstractSpin 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.
Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/15757
Collection机器人学研究室
Corresponding AuthorHe YQ(何玉庆)
Affiliation1.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
Recommended Citation
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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