Multi-object tracking with inter-feedback between detection and tracking
Tian, Shu1,2; Yuan, Fei2; Xia, Gui-Song3
2016
发表期刊NEUROCOMPUTING
卷号171页码:768-780
文章类型Article
摘要Multi-object tracking is an important but challenging task in computer. vision. Tremendous investigations have been made on the topics, among which tracking-by-detection method first detects objects independently at each frame and then links the detected objects into trajectories. One shortcoming of this method, however, lies in the fact that it regards detecting and tracking as two separated processes and the tracking information are not used in detection, which often results in many false and missing detections and involves heavy computational complexity. In order to solve this problem, this paper proposes a multi-type multi-object tracking algorithm, by introducing on-line inter-feedback information between the detection and tracking processes into the tracking-by-detection method. Our tracking algorithm consists of two iterative components: detection by feedback from tracking and Tracking based on detection. In the detection step, objects are detected by the detectors adjusted by information from tracking. In the tracking step, we use group tracking strategy based on detection. Moreover, in order to handle tracking scenarios with different complexity, objects are classified into two categories, i.e. single object and multiple ones, and are dealt with different strategies. The proposed algorithm is evaluated on several real surveillance videos and achieve higher performance in contrast to the state-of-the-art methods. Besides the high precision, it also has demonstrated that the proposed algorithm needs less detector and searching scale and can run in real time for many tracking applications. (C) 2015 Elsevier B.V. All rights reserved.
关键词Tracking-by-detection Method Feedback Real-time Multi-object Tracking
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2015.07.028
关键词[WOS]VISUAL TRACKING ; OBJECT TRACKING ; BACKGROUND SUBTRACTION ; MULTITARGET TRACKING ; PARTICLE FILTER ; MULTIPLE
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000364883900077
引用统计
被引频次:9[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/10509
专题数字内容技术与服务研究中心_听觉模型与认知计算
作者单位1.Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Wuhan Univ, State Key Lab LIESMARS, Wuhan 430079, Peoples R China
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Tian, Shu,Yuan, Fei,Xia, Gui-Song. Multi-object tracking with inter-feedback between detection and tracking[J]. NEUROCOMPUTING,2016,171:768-780.
APA Tian, Shu,Yuan, Fei,&Xia, Gui-Song.(2016).Multi-object tracking with inter-feedback between detection and tracking.NEUROCOMPUTING,171,768-780.
MLA Tian, Shu,et al."Multi-object tracking with inter-feedback between detection and tracking".NEUROCOMPUTING 171(2016):768-780.
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