Knowledge Commons of Institute of Automation,CAS
3D Tracker-Level Fusion for Robust RGB-D Tracking | |
An, Ning1,2; Zhao, Xiao-Guang1,2; Hou, Zeng-Guang1,2 | |
发表期刊 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
2017-08-01 | |
卷号 | E100D期号:8页码:1870-1881 |
文章类型 | Article |
摘要 | In 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. |
关键词 | Rgb-d Tracking Data Fusion 3d Object Tracking Online Video Processing |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1587/transinf.2016EDP7498 |
关键词[WOS] | OBJECT TRACKING ; VISUAL TRACKING ; BENCHMARK ; MODEL |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61271432 ; 61673378 ; 61421004) |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering |
WOS记录号 | WOS:000406868400036 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19942 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 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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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2{3D Tracker-Level F(5024KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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