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3D Tracker-Level Fusion for Robust RGB-D Tracking
An, Ning1,2; Zhao, Xiao-Guang1,2; Hou, Zeng-Guang1,2
Source PublicationIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
2017-08-01
VolumeE100DIssue:8Pages:1870-1881
SubtypeArticle
AbstractIn this study, we address the problem of online RGB-D tracking which confronted with various challenges caused by deformation, occlusion, background clutter, and abrupt motion. Various trackers have different strengths and weaknesses, and thus a single tracker can merely perform well in specific scenarios. We propose a 3D tracker-level fusion algorithm (TLF3D) which enhances the strengths of different trackers and suppresses their weaknesses to achieve robust tracking performance in various scenarios. The fusion result is generated from outputs of base trackers by optimizing an energy function considering both the 3D cube attraction and 3D trajectory smoothness. In addition, three complementary base RGB-D trackers with intrinsically different tracking components are proposed for the fusion algorithm. We perform extensive experiments on a large-scale RGB-D benchmark dataset. The evaluation results demonstrate the effectiveness of the proposed fusion algorithm and the superior performance of the proposed TLF3D tracker against state-of-the-art RGB-D trackers.
KeywordRgb-d Tracking Data Fusion 3d Object Tracking Online Video Processing
WOS HeadingsScience & Technology ; Technology
DOI10.1587/transinf.2016EDP7498
WOS KeywordOBJECT TRACKING ; VISUAL TRACKING ; BENCHMARK ; MODEL
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61271432 ; 61673378 ; 61421004)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering
WOS IDWOS:000406868400036
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19942
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
An, Ning,Zhao, Xiao-Guang,Hou, Zeng-Guang. 3D Tracker-Level Fusion for Robust RGB-D Tracking[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,2017,E100D(8):1870-1881.
APA An, Ning,Zhao, Xiao-Guang,&Hou, Zeng-Guang.(2017).3D Tracker-Level Fusion for Robust RGB-D Tracking.IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,E100D(8),1870-1881.
MLA An, Ning,et al."3D Tracker-Level Fusion for Robust RGB-D Tracking".IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS E100D.8(2017):1870-1881.
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