Multi-object tracking with inter-feedback between detection and tracking

CORC > 自动化研究所 > 中国科学院自动化研究所 > 数字内容技术与服务研究中心 > 听觉模型与认知计算

	Multi-object tracking with inter-feedback between detection and tracking
	Tian, Shu 1,2; Yuan, Fei2 ; Xia, Gui-Song 3
刊名	NEUROCOMPUTING
	2016
卷号	171 页码:768-780
关键词	Tracking-by-detection method Feedback Real-time Multi-object tracking
英文摘要	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.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence
研究领域[WOS]	Computer Science
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记录号	WOS:000364883900077
公开日期	2016-02-26
内容类型	期刊论文
源URL	[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
推荐引用方式 GB/T 7714	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.