Online multiple object tracking via exchanging object context

doi:10.1016/j.neucom.2018.02.068

	Online multiple object tracking via exchanging object context
	Yu, Hongyang 1; Qin, Lei 2; Huang, Qingming 1,3; Yao, Hongxun 1
	2018-05-31
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	292 页码:28-37
摘要	Multiple object tracking is a key problem for many computer vision applications such as video surveillance, advanced driver assistance or animation. Most of existing tracking-by-detection methods are mainly based on object appearances and motions. However, the contextual information around the target has not been fully exploited. In this paper, we pay more attention to the contextual information and propose an Exchanging Object Context (EOC) model, which takes full advantage of the context information. Specifically, we implement an efficient and accurate online multiple object tracking algorithm with a novel affinity measure to associate detections. This measure calculates the similarity between targets and detections with the background smoothness after exchanging the contexts between detections and targets, using a novel color histogram descriptor. We refine the bounding boxes by measuring the context changes. Extensive experimental results on two public benchmarks demonstrate the effectiveness of the proposed tracking method with comparisons to several state-of-the-art trackers. (c) 2018 Elsevier B.V. All rights reserved.
关键词	Multiple object tracking Tracking-by-detection method Exchanging object context model Online tracking
DOI	10.1016/j.neucom.2018.02.068
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[61572465] ; National Natural Science Foundation of China[61390510] ; National Natural Science Foundation of China[61732007] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[61472103] ; National Natural Science Foundation of China[61772158] ; National Natural Science Foundation of China[U1711265] ; Key Research Program of Frontier Sciences[CAS: QYZDJ-SSW-SYS013]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000429321400002
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5721
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Huang, Qingming
作者单位	1.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China 2.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Yu, Hongyang,Qin, Lei,Huang, Qingming,et al. Online multiple object tracking via exchanging object context[J]. NEUROCOMPUTING,2018,292:28-37.
APA	Yu, Hongyang,Qin, Lei,Huang, Qingming,&Yao, Hongxun.(2018).Online multiple object tracking via exchanging object context.NEUROCOMPUTING,292,28-37.
MLA	Yu, Hongyang,et al."Online multiple object tracking via exchanging object context".NEUROCOMPUTING 292(2018):28-37.