Part-based Online Tracking with Geometry Constraint and Attention Selection

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	Part-based Online Tracking with Geometry Constraint and Attention Selection
	Fang, Jianwu 1; Wang, Qi 2; Yuan, Yuan1
刊名	ieee transactions on circuits and systems for video technology
	2014-05-01
卷号	24 期号:5 页码:854-864
关键词	Attention selection multiple parts constraint object tracking online AdaBoost (OAB) relaxation factor
ISSN号	1051-8215
英文摘要	visual tracking in condition of occlusion, appearance or illumination change has been a challenging task over decades. recently, some online trackers, based on the detection by classification framework, have achieved good performance. however, problems are still embodied in at least one of the three aspects: 1) tracking the target with a single region has poor adaptability for occlusion, appearance or illumination change; 2) lack of sample weight estimation, which may cause overfitting issue; and 3) inadequate motion model to prevent target from drifting. for tackling the above problems, this paper presents the contributions as follows: 1) a novel part-based structure is utilized in the online adaboost tracking; 2) attentional sample weighting and selection is tackled by introducing a weight relaxation factor, instead of treating the samples equally as traditional trackers do; and 3) a two-stage motion model, multiple parts constraint, is proposed and incorporated into the part-based structure to ensure a stable tracking. the effectiveness and efficiency of the proposed tracker is validated upon several complex video sequences, compared with seven popular online trackers. the experimental results show that the proposed tracker can achieve increased accuracy with comparable computational cost.
WOS标题词	science & technology ; technology
类目[WOS]	engineering, electrical & electronic
研究领域[WOS]	engineering
关键词[WOS]	real-time tracking ; object tracking ; visual tracking ; nonrigid object ; robust tracking ; mean shift ; features ; color
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000336057400012
公开日期	2015-03-18
内容类型	期刊论文
源URL	[http://ir.opt.ac.cn/handle/181661/22355]
专题	西安光学精密机械研究所_光学影像学习与分析中心
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Xian 710072, Peoples R China
推荐引用方式 GB/T 7714	Fang, Jianwu,Wang, Qi,Yuan, Yuan. Part-based Online Tracking with Geometry Constraint and Attention Selection[J]. ieee transactions on circuits and systems for video technology,2014,24(5):854-864.
APA	Fang, Jianwu,Wang, Qi,&Yuan, Yuan.(2014).Part-based Online Tracking with Geometry Constraint and Attention Selection.ieee transactions on circuits and systems for video technology,24(5),854-864.
MLA	Fang, Jianwu,et al."Part-based Online Tracking with Geometry Constraint and Attention Selection".ieee transactions on circuits and systems for video technology 24.5(2014):854-864.