A Robust Tracking System for Low Frame Rate Video

doi:10.1007/s11263-015-0819-8

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 视频内容安全

	A Robust Tracking System for Low Frame Rate Video
	Zhang, Xiaoqin 1; Hu, Weiming2 ; Xie, Nianhua 2; Bao, Hujun 3; Maybank, Stephen 4
发表期刊	INTERNATIONAL JOURNAL OF COMPUTER VISION
	2015-12-01
卷号	115 期号:3 页码:279-304
文章类型	Article
摘要	Tracking 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.
关键词	Low Frame Rate Tracking Dominant Color Bin-ratio Matching Metric Particle Swarm Optimization
WOS标题词	Science & Technology ; Technology
DOI	10.1007/s11263-015-0819-8
关键词[WOS]	VISUAL TRACKING ; PARTICLE FILTERS ; OBJECT TRACKING ; MODELS ; RECOGNITION
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:000365089800003
引用统计	被引频次：74[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/173211/10511
专题	多模态人工智能系统全国重点实验室_视频内容安全
作者单位	1.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
推荐引用方式 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.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
A robust tracking sy（2788KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载