Tracking vehicles as groups in airborne videos

doi:10.1016/j.neucom.2012.05.026

OPT OpenIR > 光谱成像技术研究室

	Tracking vehicles as groups in airborne videos
	Cao, Xianbin 2,3; Shi, Zhengrong 4; Yan, Pingkun 1; Li, Xuelong1
作者部门	光学影像学习与分析中心
	2013
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	99 页码:38-45
产权排序	1
摘要	Airborne vehicle tracking system is receiving increasing attention due to its high mobility, low cost and large surveillance scope. However, tracking multiple vehicles simultaneously on airborne platform is a challenging problem, owing to camera vibration, which causes visible frame-to-frame jitter in the airborne videos and uncertain vehicle motion. To address these problems, a new collaborative tracking framework is proposed in this paper. The framework consists of a two-level tracking process to track vehicles as groups. The higher level builds the relevance network and divides target vehicles into different groups, where the relevance is calculated based on the status information of vehicles obtained from the lower level. The proposed group tracking takes into account the relevance between vehicles and reduces the impact of camera vibration. Experimental results demonstrated that the proposed method has better performance in terms of tracking speed and tracking accuracy compared to other existing approaches based on particle filter and stationary grouping. (C) 2012 Elsevier B.V. All rights reserved.
文章类型	Article
关键词	Group Tracking Relevance Network Kalman Filter Airborne Platforms Multi-target Tracking
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.neucom.2012.05.026
收录类别	SCI ; EI
关键词[WOS]	VISUAL TRACKING ; MEAN SHIFT ; OBJECT
语种	英语
WOS研究方向	Computer Science
项目资助者	National Basic Research Program of China (973 Program)(2011CB707000) ; National Natural Science Foundation of China(61072093 ; Open Project Foundation of the Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences(20090101) ; 61125106 ; 91120302)
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000311129300004
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/23179
专题	光谱成像技术研究室
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.BeiHang Univ, Sch Elect Informat Engn, Beijing 100191, Peoples R China 3.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China 4.Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei 230026, Peoples R China
推荐引用方式 GB/T 7714	Cao, Xianbin,Shi, Zhengrong,Yan, Pingkun,et al. Tracking vehicles as groups in airborne videos[J]. NEUROCOMPUTING,2013,99:38-45.
APA	Cao, Xianbin,Shi, Zhengrong,Yan, Pingkun,&Li, Xuelong.(2013).Tracking vehicles as groups in airborne videos.NEUROCOMPUTING,99,38-45.
MLA	Cao, Xianbin,et al."Tracking vehicles as groups in airborne videos".NEUROCOMPUTING 99(2013):38-45.

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