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A Robust Tracking System for Low Frame Rate Video
Zhang, Xiaoqin1; Hu, Weiming2; Xie, Nianhua2; Bao, Hujun3; Maybank, Stephen4
Source PublicationINTERNATIONAL JOURNAL OF COMPUTER VISION
2015-12-01
Volume115Issue:3Pages:279-304
SubtypeArticle
AbstractTracking in low frame rate (LFR) videos is one of the most important problems in the tracking literature. Most existing approaches treat LFR video tracking as an abrupt motion tracking problem. However, in LFR video tracking applications, LFR not only causes abrupt motions, but also large appearance changes of objects because the objects' poses and the illumination may undergo large changes from one frame to the next. This adds extra difficulties to LFR video tracking. In this paper, we propose a robust and general tracking system for LFR videos. The tracking system consists of four major parts: dominant color-spatial based object representation, bin-ratio based similarity measure, annealed particle swarm optimization (PSO) based searching, and an integral image based parameter calculation. The first two parts are combined to provide a good solution to the appearance changes, and the abrupt motion is effectively captured by the annealed PSO based searching. Moreover, an integral image of model parameters is constructed, which provides a look-up table for parameters calculation. This greatly reduces the computational load. Experimental results demonstrate that the proposed tracking system can effectively tackle the difficulties caused by LFR.
KeywordLow Frame Rate Tracking Dominant Color Bin-ratio Matching Metric Particle Swarm Optimization
WOS HeadingsScience & Technology ; Technology
DOI10.1007/s11263-015-0819-8
WOS KeywordVISUAL TRACKING ; PARTICLE FILTERS ; OBJECT TRACKING ; MODELS ; RECOGNITION
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000365089800003
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10511
Collection模式识别国家重点实验室_视频内容安全
Affiliation1.Wenzhou Univ, Inst Intelligent Syst & Decis, Hangzhou, Zhejiang, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Zhejiang Univ, Dept Comp Sci, Hangzhou, Zhejiang, Peoples R China
4.Birkbeck Coll, Dept Comp Sci & Informat Syst, London, England
Recommended Citation
GB/T 7714
Zhang, Xiaoqin,Hu, Weiming,Xie, Nianhua,et al. A Robust Tracking System for Low Frame Rate Video[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2015,115(3):279-304.
APA Zhang, Xiaoqin,Hu, Weiming,Xie, Nianhua,Bao, Hujun,&Maybank, Stephen.(2015).A Robust Tracking System for Low Frame Rate Video.INTERNATIONAL JOURNAL OF COMPUTER VISION,115(3),279-304.
MLA Zhang, Xiaoqin,et al."A Robust Tracking System for Low Frame Rate Video".INTERNATIONAL JOURNAL OF COMPUTER VISION 115.3(2015):279-304.
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