P2T: Part-to-Target Tracking via Deep Regression Learning
文献类型:期刊论文
作者 | Gao, Junyu1,2![]() ![]() ![]() ![]() |
刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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出版日期 | 2018-06 |
卷号 | 27期号:6页码:3074-3086 |
关键词 | Visual Tracking Deep Learning Part-based Tracker |
DOI | 10.1109/TIP.2018.2813166 |
文献子类 | Article |
英文摘要 | Most existing part-based tracking methods are part-to-part trackers, which usually have two separated steps including the part matching and target localization. Different from existing methods, in this paper, we propose a novel part-to-target (P2T) tracker in a unified fashion by inferring target location from parts directly. To achieve this goal, we propose a novel deep regression model for P2T regression in an end-to-end framework via convolutional neural networks. The proposed model is designed not only to exploit the part context information to preserve object spatial layout structure, but also to learn part reliability to emphasize part importance for the robust P2T regression. We evaluate the proposed tracker on four challenging benchmark sequences, and extensive experimental results demonstrate that our method performs favorably against state-of-the-art trackers because of the powerful capacity of the proposed deep regression model. |
WOS关键词 | ROBUST VISUAL TRACKING ; OBJECT TRACKING ; BENCHMARK ; MODEL |
WOS研究方向 | Computer Science ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000428930600014 |
资助机构 | National Natural Science Foundation of China(61432019 ; Key Research Program of Frontier Sciences, CAS(QYZDJ-SSW-JSC039) ; Beijing Natural Science Foundation(4172062) ; 61572498 ; 61532009 ; 61702511 ; 61572296) |
源URL | [http://ir.ia.ac.cn/handle/173211/21999] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Gao, Junyu,Zhang, Tianzhu,Yang, Xiaoshan,et al. P2T: Part-to-Target Tracking via Deep Regression Learning[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,27(6):3074-3086. |
APA | Gao, Junyu,Zhang, Tianzhu,Yang, Xiaoshan,&Xu, Changsheng.(2018).P2T: Part-to-Target Tracking via Deep Regression Learning.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(6),3074-3086. |
MLA | Gao, Junyu,et al."P2T: Part-to-Target Tracking via Deep Regression Learning".IEEE TRANSACTIONS ON IMAGE PROCESSING 27.6(2018):3074-3086. |
入库方式: OAI收割
来源:自动化研究所
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