A robust tracker integrating particle filter into correlation filter framework

doi:10.1007/s11042-020-09240-7

CORC > 兰州理工大学 > 兰州理工大学 > 党委教师工作部（人事处、教师发展中心）

	A robust tracker integrating particle filter into correlation filter framework
	Liu, Weirong 1; Gao, Huiling 1; Liu, Jie 2; Liu, Chaorong 3; Li, Binshan 1; Song, Xuhui 1
刊名	Multimedia Tools and Applications
	2020-10-01
卷号	79 期号:37-38 页码:28431-28452
关键词	Monte Carlo methods Rotation Correlation filters Fixed intervals Particle filter Rotation factors Scale and rotation Target position Tracking failure Update schemes
ISSN号	13807501
DOI	10.1007/s11042-020-09240-7
英文摘要	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.
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	Springer
WOS记录号	WOS:000555361800004
内容类型	期刊论文
源URL	[http://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
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou City, China; 2.National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou City, China; 3.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou City, China
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.