Visual Tracking Based on Dynamic Coupled Conditional Random Field Model

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	Visual Tracking Based on Dynamic Coupled Conditional Random Field Model
	Liu, Yuqiang1,2 ; Wang, Kunfeng1 ; Shen, Dayong 3
刊名	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2016-03-01
卷号	17 期号:3 页码:822-833
关键词	Coupled conditional random field dynamic models visual tracking region-level tracking spatiotemporal context
通讯作者	Wang, Kunfeng(王坤峰)
英文摘要	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.
学科主题	CIVIL ENGINEERING
WOS标题词	Science & Technology ; Technology
类目[WOS]	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
研究领域[WOS]	Engineering ; Transportation
关键词[WOS]	VEHICLE DETECTION ; OBJECT TRACKING ; SEGMENTATION ; VIDEO ; INFORMATION ; INTEGRATION ; OCCLUSIONS ; BEHAVIOR ; FLOW
收录类别	SCI
原文出处	http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7307175&filter%3DAND%28p_IS_Number%3A7420563%29
语种	英语
WOS记录号	WOS:000371982600019
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/10860]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
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
推荐引用方式 GB/T 7714	Liu, Yuqiang,Wang, Kunfeng,Shen, Dayong. 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.(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.