Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking

doi:10.1109/TMM.2018.2872897

	Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking
	Ruan, Weijian 1,2; Chen, Jun 1,2; Wu, Yi 3,4; Wang, Jinqiao5 ; Liang, Chao 1,2; Hu, Ruimin 1,2; Jiang, Junjun 6,7
刊名	IEEE TRANSACTIONS ON MULTIMEDIA
	2019-05-01
卷号	21 期号:5 页码:1122-1134
关键词	Correlation filters partial occlusions triangle structure high energy high integrity
ISSN号	1520-9210
DOI	10.1109/TMM.2018.2872897
通讯作者	Chen, Jun(chenj.whu@gmail.com)
英文摘要	Correlation filters (CFs) have been extensively used in tracking tasks due to their high efficiency although most of them regard the tracked target as a whole and are minimally effective in handling partial occlusion. In this study, we incorporate a part-based strategy into the framework of CFs and propose a novel multipart correlation tracker with triangle-structure constraints. Specifically, we train multiple CFs for the global object and local parts, which are then jointly applied to obtain the correlation response of any candidate during tracking. The tracker is robust in handling partial occlusion because of the use of part-based representation. The remaining global representation can contribute reliable cues in cases wherein several local filters drift away in a specific scene. We further propose a triangle-structure model to measure the structural similarity of candidates. The model employs multiple triangles to determine the spatial relationship among parts and helps constrain the location of the target. Moreover, we introduce an effective part selection scheme based on energy and integrity, which is generally applicable to part-tracking models. Extensive experiments on two public benchmarks demonstrate the superiority of the proposed method over the state-of-the-art approaches.
资助项目	National Nature Science Foundation of China[U1611461] ; National Nature Science Foundation of China[61876135] ; National Nature Science Foundation of China[61876086] ; National Key R&D Program of China[2017YFC0803700] ; Hubei Province Technological Innovation Major Project[2017AAA123] ; Hubei Province Technological Innovation Major Project[2018AAA062] ; Nature Science Foundation of Jiangsu Province[BK20160386]
WOS关键词	VISUAL TRACKING ; NONRIGID OBJECT
WOS研究方向	Computer Science ; Telecommunications
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000466223600004
资助机构	National Nature Science Foundation of China ; National Key R&D Program of China ; Hubei Province Technological Innovation Major Project ; Nature Science Foundation of Jiangsu Province
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/24209]
专题	中国科学院自动化研究所
通讯作者	Chen, Jun
作者单位	1.Wuhan Univ, Sch Comp, Natl Engn Res Ctr Multimedia Software, Wuhan 430072, Hubei, Peoples R China 2.Collaborat Innovat Ctr Geospatial Technol, Wuhan 430072, Hubei, Peoples R China 3.CuraCloud Corp, Seattle, WA 98104 USA 4.Nanjing Audit Univ, Nanjing 211815, Jiangsu, Peoples R China 5.Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 6.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Heilongjiang, Peoples R China 7.Peng Cheng Lab, Shenzhen, Peoples R China
推荐引用方式 GB/T 7714	Ruan, Weijian,Chen, Jun,Wu, Yi,et al. Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2019,21(5):1122-1134.
APA	Ruan, Weijian.,Chen, Jun.,Wu, Yi.,Wang, Jinqiao.,Liang, Chao.,...&Jiang, Junjun.(2019).Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking.IEEE TRANSACTIONS ON MULTIMEDIA,21(5),1122-1134.
MLA	Ruan, Weijian,et al."Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking".IEEE TRANSACTIONS ON MULTIMEDIA 21.5(2019):1122-1134.