CASIA OpenIR
Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning
Gao, Jin1; Wang, Qiang1; Xing, Junliang1; Ling, Haibin2; Hu, Weiming1; Maybank, Stephen3
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN0162-8828
2020-04-01
Volume42Issue:4Pages:939-955
Corresponding AuthorHu, Weiming(wmhu@nlpr.ia.ac.cn)
AbstractThis paper presents a new Gaussian Processes (GPs)-based particle filter tracking framework. The framework non-trivially extends Gaussian process regression (GPR) to transfer learning, and, following the tracking-by-fusion strategy, integrates closely two tracking components, namely a GPs component and a CFs one. First, the GPs component analyzes and models the probability distribution of the object appearance by exploiting GPs. It categorizes the labeled samples into auxiliary and target ones, and explores unlabeled samples in transfer learning. The GPs component thus captures rich appearance information over object samples across time. On the other hand, to sample an initial particle set in regions of high likelihood through the direct simulation method in particle filtering, the powerful yet efficient correlation filters (CFs) are integrated, leading to the CFs component. In fact, the CFs component not only boosts the sampling quality, but also benefits from the GPs component, which provides re-weighted knowledge as latent variables for determining the impact of each correlation filter template from the auxiliary samples. In this way, the transfer learning based fusion enables effective interactions between the two components. Superior performance on four object tracking benchmarks (OTB-2015, Temple-Color, and VOT2015/2016), and in comparison with baselines and recent state-of-the-art trackers, has demonstrated clearly the effectiveness of the proposed framework.
KeywordTask analysis Correlation Target tracking Probability distribution Visualization Collaboration Visual tracking Gaussian processes correlation filters transfer learning tracking-by-fusion
DOI10.1109/TPAMI.2018.2889070
WOS KeywordVISUAL TRACKING ; OBJECT TRACKING ; NETWORKS
Indexed BySCI
Language英语
Funding ProjectNatural Science Foundation of China[61602478] ; Natural Science Foundation of China[61751212] ; Natural Science Foundation of China[61472421] ; Beijing Natural Science Foundation[L172051] ; NSFC-general technology collaborative Fund for basic research[U1636218] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC040] ; CAS External cooperation key project ; Research Project of ForwardX Robotics, Inc. ; US NSF[1350521] ; US NSF[1618398] ; US NSF[1814745]
Funding OrganizationNatural Science Foundation of China ; Beijing Natural Science Foundation ; NSFC-general technology collaborative Fund for basic research ; Key Research Program of Frontier Sciences, CAS ; CAS External cooperation key project ; Research Project of ForwardX Robotics, Inc. ; US NSF
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000526541100011
PublisherIEEE COMPUTER SOC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/38908
Collection中国科学院自动化研究所
Corresponding AuthorHu, Weiming
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
2.Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA
3.Birkbeck Coll, Dept Comp Sci & Informat Syst, Malet St, London WC1E 7HX, England
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Gao, Jin,Wang, Qiang,Xing, Junliang,et al. Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2020,42(4):939-955.
APA Gao, Jin,Wang, Qiang,Xing, Junliang,Ling, Haibin,Hu, Weiming,&Maybank, Stephen.(2020).Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,42(4),939-955.
MLA Gao, Jin,et al."Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 42.4(2020):939-955.
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