CASIA OpenIR
Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking
Ruan, Weijian1,2; Chen, Jun1,2; Wu, Yi3,4; Wang, Jinqiao5; Liang, Chao1,2; Hu, Ruimin1,2; Jiang, Junjun6,7
Source PublicationIEEE TRANSACTIONS ON MULTIMEDIA
ISSN1520-9210
2019-05-01
Volume21Issue:5Pages:1122-1134
Corresponding AuthorChen, Jun(chenj.whu@gmail.com)
AbstractCorrelation 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.
KeywordCorrelation filters partial occlusions triangle structure high energy high integrity
DOI10.1109/TMM.2018.2872897
WOS KeywordVISUAL TRACKING ; NONRIGID OBJECT
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational Nature Science Foundation of China ; National Key R&D Program of China ; Hubei Province Technological Innovation Major Project ; Nature Science Foundation of Jiangsu Province
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS IDWOS:000466223600004
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24210
Collection中国科学院自动化研究所
Corresponding AuthorChen, Jun
Affiliation1.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
Recommended Citation
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.
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