Underwater image matching by incorporating structural constraints

doi:10.1177/1729881417738100

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Underwater image matching by incorporating structural constraints
	Yang, Xu1 ; Liu, Zhi-Yong1,2,3 ; Qiao, Hong1,2,3 ; Song, Yong-Bo 1; Ren, Shu-Nan1 ; Ji, Da-Xiong 4; Zheng, Sui-Wu1,5
发表期刊	INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
	2017-12-20
卷号	14 期号:6 页码:0
文章类型	Article
摘要	Underwater robot plays an important role in underwater perception and manipulation tasks. Vision information processing is essential for the intelligent perception of an underwater robot, in which image matching is a fundamental topic. Feature-based image matching is suitable for the underwater environment. However, current underwater image matching usually directly applies those methods with a general purpose or designed for images obtained from the land to underwater images. The problem is that the blurring appearance caused feature descriptor ambiguity, which may greatly deteriorate the performance of these methods on underwater images. Aiming at problem, this article provides an underwater image matching framework by incorporating structural constraints. By integrating the appearance descriptor and structural information by a graph model, the feature correspondence-based image matching is formulated and solved by a graph matching method. Particularly, to solve the outlier feature problem, the graph matching method is applicable to the case where outlier features exist in both underwater images. Experiments on both synthetic points and real-world underwater images validate the effectiveness of the proposed method.
其他摘要	无
关键词	Underwater Image Image Matching Underwater Robot Feature Correspondence
WOS标题词	Science & Technology ; Technology
DOI	10.1177/1729881417738100
关键词[WOS]	GRAPH ; GNCCP
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61503383 ; National Key Research and Development Plan of China(2016YFC0300801) ; Beijing Municipal Science and Technology(D16110400140000 ; Guangdong Science and Technology Department(2016B090910001) ; 61633009 ; D161100001416001) ; U1613213 ; 61375005 ; 61210009 ; 61773047)
WOS研究方向	Robotics
WOS类目	Robotics
WOS记录号	WOS:000418542000001
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15487
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Zhongguancun East Rd 95, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Zhejiang Univ, Ocean Coll, Zhoushan, Peoples R China 5.Huizhou Adv Mfg Technol Res Ctr Co Ltd, Huizhou 516000, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Yang, Xu,Liu, Zhi-Yong,Qiao, Hong,et al. Underwater image matching by incorporating structural constraints[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2017,14(6):0.
APA	Yang, Xu.,Liu, Zhi-Yong.,Qiao, Hong.,Song, Yong-Bo.,Ren, Shu-Nan.,...&Zheng, Sui-Wu.(2017).Underwater image matching by incorporating structural constraints.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,14(6),0.
MLA	Yang, Xu,et al."Underwater image matching by incorporating structural constraints".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 14.6(2017):0.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Underwater Image Mat（57KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览