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Search inliers based on redundant geometric constraints
Lu RR(鲁荣荣)1,2,3,4; Zhu F(朱枫)1,3,4; Wu QX(吴清潇)1,3,4; Fu XY(付兴银)1,2,3,4
Source PublicationVisual Computer
Indexed BySCI ; EI
EI Accession number20184506033543
WOS IDWOS:000511910300003
Contribution Rank1
Funding OrganizationNSFC (U1713216) ; Autonomous subject of the State Key Laboratory of Robotics (2017-Z21)
KeywordCorrespondence grouping Geometric constraints Correspondence voting 3D object recognition

This paper presents an efficient correspondence grouping algorithm to search inliers from an initial set of feature matches. The novelty lies in the proposal of a scoring technique for measuring the reliability of a triple combination (three pairs of matches) based on redundant geometric constraints. According to the proposed scoring method, several top-ranking triple combinations are selected for estimating the transformation hypotheses between two 3D shapes. For each transformation hypothesis, a correspondence from a selected correspondence set should cast a vote whether it is satisfying the geometric constraint with it. Finally, the transformation hypothesis with the most votes is considered as the best transformation and the correspondences from the initial correspondence set agreeing with the best transformation are grouped as inliers. We performed both comparative experiments and real application experiments to evaluate the performance of our proposed method on five popular datasets. The experimental results show the superior performance of our method with respect to different levels of noise, point density variation, partial overlap, clutter and occlusion. In addition, our proposed method can boost the performance of a feature-based 3D object recognition algorithm, giving an increase in both high recognition rate and computational efficiency.

WOS SubjectComputer Science, Software Engineering
WOS Research AreaComputer Science
Funding ProjectNSFC[U1713216] ; Autonomous subject of the State Key Laboratory of Robotics[2017-Z21]
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorLu RR(鲁荣荣); Zhu F(朱枫)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China
4.The Key Lab of Image Understanding and Computer Vision, Shenyang
5.Liaoning Province 110016, China
Recommended Citation
GB/T 7714
Lu RR,Zhu F,Wu QX,et al. Search inliers based on redundant geometric constraints[J]. Visual Computer,2020,36(2):253-266.
APA Lu RR,Zhu F,Wu QX,&Fu XY.(2020).Search inliers based on redundant geometric constraints.Visual Computer,36(2),253-266.
MLA Lu RR,et al."Search inliers based on redundant geometric constraints".Visual Computer 36.2(2020):253-266.
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