Visual Tracking Based on Dynamic Coupled Conditional Random Field Model
Liu, Yuqiang1,2; Wang, Kunfeng1; Shen, Dayong3; Wang, Kunfeng(王坤峰)
2016-03-01
发表期刊IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
卷号17期号:3页码:822-833
文章类型Article
摘要This paper proposes a novel approach to visual tracking of moving objects based on the dynamic coupled conditional random field (DcCRF) model. The principal idea is to integrate a variety of relevant knowledge about object tracking into a unified dynamic probabilistic framework, which is called the DcCRF model in this paper. Under this framework, the proposed approach integrates spatiotemporal contextual information of motion and appearance, as well as the compatibility between the foreground label and object label. An approximate inference algorithm, i.e., loopy belief propagation, is adopted to conduct the inference. Meanwhile, the background model is adaptively updated to deal with gradual background changes. Experimental results show that the proposed approach can accurately track moving objects (with or without occlusions) in monocular video sequences and outperforms some state-of-the-art methods in tracking and segmentation accuracy.
关键词Coupled Conditional Random Field Dynamic Models Visual Tracking Region-level Tracking Spatiotemporal Context
WOS标题词Science & Technology ; Technology
学科领域Civil Engineering
DOI10.1109/TITS.2015.2488287
关键词[WOS]VEHICLE DETECTION ; OBJECT TRACKING ; SEGMENTATION ; VIDEO ; INFORMATION ; INTEGRATION ; OCCLUSIONS ; BEHAVIOR ; FLOW
URL查看原文
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61304200) ; MIIT Project of Internet of Things Development Fund(1F15E02)
WOS研究方向Engineering ; Transportation
WOS类目Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号WOS:000371982600019
引用统计
被引频次:5[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/173211/10860
专题复杂系统管理与控制国家重点实验室_先进控制与自动化
通讯作者Wang, Kunfeng(王坤峰)
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
3.Natl Univ Def Technol, Res Ctr Computat Expt & Parallel Syst, Changsha 410073, Hunan, Peoples R China
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Liu, Yuqiang,Wang, Kunfeng,Shen, Dayong,et al. Visual Tracking Based on Dynamic Coupled Conditional Random Field Model[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2016,17(3):822-833.
APA Liu, Yuqiang,Wang, Kunfeng,Shen, Dayong,&Wang, Kunfeng.(2016).Visual Tracking Based on Dynamic Coupled Conditional Random Field Model.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,17(3),822-833.
MLA Liu, Yuqiang,et al."Visual Tracking Based on Dynamic Coupled Conditional Random Field Model".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 17.3(2016):822-833.
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