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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
作者部门光电信息技术研究室
关键词Correspondence grouping Geometric constraints Correspondence voting 3D object recognition
发表期刊Visual Computer
ISSN0178-2789
2018
页码1-14
收录类别EI
EI收录号20184506033543
产权排序1
资助机构NSFC (U1713216) ; Autonomous subject of the State Key Laboratory of Robotics (2017-Z21)
摘要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.
语种英语
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/23551
专题光电信息技术研究室
通讯作者Lu RR(鲁荣荣); Zhu F(朱枫)
作者单位1.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
推荐引用方式
GB/T 7714
Lu RR,Zhu F,Wu QX,et al. Search inliers based on redundant geometric constraints[J]. Visual Computer,2018:1-14.
APA Lu RR,Zhu F,Wu QX,&Fu XY.(2018).Search inliers based on redundant geometric constraints.Visual Computer,1-14.
MLA Lu RR,et al."Search inliers based on redundant geometric constraints".Visual Computer (2018):1-14.
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