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

文献类型：期刊论文

作者Ruan, Weijian1,2; Chen, Jun1,2; Wu, Yi3,4; Wang, Jinqiao5; Liang, Chao1,2; Hu, Ruimin1,2; Jiang, Junjun6,7
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2019-05-01
卷号21期号:5页码:1122-1134
ISSN号1520-9210
关键词Correlation filters partial occlusions triangle structure high energy high integrity
DOI10.1109/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.
WOS关键词VISUAL TRACKING ; NONRIGID OBJECT
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
源URL[http://ir.ia.ac.cn/handle/173211/24209]  
专题自动化研究所_模式识别国家重点实验室_图像与视频分析团队
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.

入库方式： OAI收割

来源：自动化研究所

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