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BB-Homography: Joint Binary Features and Bipartite Graph Matching for Homography Estimation
Liu, Shaoguo1; Wang, Haibo2; Wei, Yiyi1; Pan, Chunhong1
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
2015-02-01
Volume25Issue:2Pages:239-250
SubtypeArticle
AbstractHomography estimation is a fundamental problem in the field of computer vision. For estimating the homography between two images, one of the key issues is to match keypoints in the reference image to the keypoints in the moving image. To match keypoints in real time, a binary image descriptor, due to its low matching and storage costs, emerges as a more and more popular tool. Upon achieving the low costs, the binary descriptor sacrifices the discriminative power of using floating points. In this paper, we present BB-Homography, a new approach that fuses fast binary descriptor matching and bipartite graph for homography estimation. Starting with binary descriptor matching, BB-Homography uses bipartite graph matching (GM) algorithm to refine the matching results, which are finally passed over to estimate homography. On realizing the correlation between keypoint correspondence and homography estimation, BB-Homography iteratively performs the GM and the homography estimation such that they can refine each other at each iteration. In particular, based on spectral graph, a fast bipartite GM algorithm is developed for lowering the time cost of BB-Homography. BB-Homography is extensively evaluated on both public benchmarks and live-captured video streams that consistently shows that BB-Homography outperforms conventional methods for homography estimation.
KeywordBb-homography Binary Feature Descriptor Graph Matching (Gm) Homography Sparse Spectral Gm
WOS HeadingsScience & Technology ; Technology
WOS KeywordDESCRIPTORS
Indexed BySCI
Language英语
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000349624000006
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8060
Collection模式识别国家重点实验室_先进数据分析与学习
Affiliation1.Chinese Acad Sci, Inst Automat, IGIT Grp, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Shandong Univ, Sch Control Sci & Engn, Robot Ctr, Jinan 250100, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Liu, Shaoguo,Wang, Haibo,Wei, Yiyi,et al. BB-Homography: Joint Binary Features and Bipartite Graph Matching for Homography Estimation[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2015,25(2):239-250.
APA Liu, Shaoguo,Wang, Haibo,Wei, Yiyi,&Pan, Chunhong.(2015).BB-Homography: Joint Binary Features and Bipartite Graph Matching for Homography Estimation.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,25(2),239-250.
MLA Liu, Shaoguo,et al."BB-Homography: Joint Binary Features and Bipartite Graph Matching for Homography Estimation".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 25.2(2015):239-250.
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