CASIA OpenIR  > 多模态人工智能系统全国重点实验室
An Accurate Outlier Rejection Network With Higher Generalization Ability for Point Cloud Registration
Guo, Shiyi1,2; Tang, Fulin1; Liu, Bingxi3; Fu, Yujie1,2; Wu, Yihong1,2
Source PublicationIEEE ROBOTICS AND AUTOMATION LETTERS
ISSN2377-3766
2023-08-01
Volume8Issue:8Pages:4649-4656
Abstract

Feature-based point cloud registration algorithms have gained more attention recently for their high robustness. Outlier rejection is a key step of such algorithms. With the development of deep learning, some of the learning-based outlier rejection methods have been proposed and implemented in various scenes. However, generalization ability and accuracy of the existing methods in complex scenes still need to be improved. In this letter, we construct a neural network for removing outlier correspondences. Particularly, we propose a novel seed selection method based on feature consistency (FC) and a new loss function based on second order feature consistency (FC$<^>{2}$). Experimental results on various datasets show the proposed network achieves better accuracy and stronger generalization ability than the state-of-the-art learning-based algorithms.

KeywordPoint cloud registration Three-dimensional displays Feature extraction Correlation Learning systems Task analysis Robustness 3D feature outlier rejection
DOI10.1109/LRA.2023.3286168
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[62202468] ; National Natural Science Foundation of China[61836015] ; National Natural Science Foundation of China[62002359]
Funding OrganizationNational Natural Science Foundation of China
WOS Research AreaRobotics
WOS SubjectRobotics
WOS IDWOS:001021244900003
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
IS Representative Paper
Sub direction classification三维视觉
planning direction of the national heavy laboratory视觉信息处理
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/53640
Collection多模态人工智能系统全国重点实验室
Corresponding AuthorWu, Yihong
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Peng Cheng Lab, Shenzhen 518066, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Guo, Shiyi,Tang, Fulin,Liu, Bingxi,et al. An Accurate Outlier Rejection Network With Higher Generalization Ability for Point Cloud Registration[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2023,8(8):4649-4656.
APA Guo, Shiyi,Tang, Fulin,Liu, Bingxi,Fu, Yujie,&Wu, Yihong.(2023).An Accurate Outlier Rejection Network With Higher Generalization Ability for Point Cloud Registration.IEEE ROBOTICS AND AUTOMATION LETTERS,8(8),4649-4656.
MLA Guo, Shiyi,et al."An Accurate Outlier Rejection Network With Higher Generalization Ability for Point Cloud Registration".IEEE ROBOTICS AND AUTOMATION LETTERS 8.8(2023):4649-4656.
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