A robust tracker integrating particle filter into correlation filter framework

doi:10.1007/s11042-020-09240-7

	A robust tracker integrating particle filter into correlation filter framework
	Liu, Weirong1 ; Gao, Huiling 1; Liu, Jie 2; Liu, Chaorong3 ; Li, Binshan 1; Song, Xuhui 1
	2020-10
发表期刊	Multimedia Tools and Applications
ISSN	13807501
卷号	79 期号:37-38 页码:28431-28452
摘要	The location and scale filters in discriminative correlation filter methods are lack of accurate rotation representation capability and updated with fixed intervals, which leads to tracking failure and time-consuming in complex scenarios. In this manuscript, a robust tracker integrating particle filter into correlation filter is presented to cope with sharp rotation and remarkable deformation. The target position and scale factor are firstly estimated from the correlation filter, and then the rotation factor is determined by similarity between candidates and template based on the particle filter. As a result, target variation can be accurately described with position, scale and rotation factor. Moreover, a long-time and short-time update scheme is proposed to solve target template drifting problem. Extensive experimental results conducted on OTB-2013, OTB-2015 and VOT-2016 show that the proposed tracker improves the accuracy and robustness of discriminative correlation filter methods. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
关键词	Monte Carlo methods Rotation Correlation filters Fixed intervals Particle filter Rotation factors Scale and rotation Target position Tracking failure Update schemes
DOI	10.1007/s11042-020-09240-7
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000555361800004
出版者	Springer
EI入藏号	20203209010855
EI主题词	Correlation methods
EI分类号	922.2 Mathematical Statistics ; 931.1 Mechanics
来源库	WOS
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/150851
专题	党委教师工作部（人事处、教师发展中心）电气工程与信息工程学院
通讯作者	Liu, Weirong
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Peoples R China; 2.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou, Peoples R China; 3.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou, Peoples R China
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院
第一作者的第一单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Liu, Weirong,Gao, Huiling,Liu, Jie,et al. A robust tracker integrating particle filter into correlation filter framework[J]. Multimedia Tools and Applications,2020,79(37-38):28431-28452.
APA	Liu, Weirong,Gao, Huiling,Liu, Jie,Liu, Chaorong,Li, Binshan,&Song, Xuhui.(2020).A robust tracker integrating particle filter into correlation filter framework.Multimedia Tools and Applications,79(37-38),28431-28452.
MLA	Liu, Weirong,et al."A robust tracker integrating particle filter into correlation filter framework".Multimedia Tools and Applications 79.37-38(2020):28431-28452.

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