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Online multiple instance gradient feature selection for robust visual tracking

文献类型：期刊论文

作者Xie, Yuan2; Qu, Yanyun1; Li, Cuihua1; Zhang, Wensheng2
刊名PATTERN RECOGNITION LETTERS
出版日期2012-07-01
卷号33期号:9页码:1075-1082
关键词Gradient-based feature selection HOG Multiple Instance Learning Online object tracking
英文摘要In this paper, we focus on learning an adaptive appearance model robustly and effectively for object tracking. There are two important factors to affect object tracking, the one is how to represent the object using a discriminative appearance model, the other is how to update appearance model in an appropriate manner. In this paper, following the state-of-the-art tracking techniques which treat object tracking as a binary classification problem, we firstly employ a new gradient-based Histogram of Oriented Gradient (HOG) feature selection mechanism under Multiple Instance Learning (MIL) framework for constructing target appearance model, and then propose a novel optimization scheme to update such appearance model robustly. This is an unified framework that not only provides an efficient way of selecting the discriminative feature set which forms a powerful appearance model, but also updates appearance model in online MIL Boost manner which could achieve robust tracking overcoming the drifting problem. Experiments on several challenging video sequences demonstrate the effectiveness and robustness of our proposal. (C) 2012 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
收录类别SCI
语种英语
WOS记录号WOS:000304235500007
公开日期2015-09-22
源URL[http://ir.ia.ac.cn/handle/173211/8007]  
专题精密感知与控制研究中心_精密感知与控制
作者单位1.Xiamen Univ, Dept Comp Sci, Video & Image Lab, Xiamen 361005, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Xie, Yuan,Qu, Yanyun,Li, Cuihua,et al. Online multiple instance gradient feature selection for robust visual tracking[J]. PATTERN RECOGNITION LETTERS,2012,33(9):1075-1082.
APA Xie, Yuan,Qu, Yanyun,Li, Cuihua,&Zhang, Wensheng.(2012).Online multiple instance gradient feature selection for robust visual tracking.PATTERN RECOGNITION LETTERS,33(9),1075-1082.
MLA Xie, Yuan,et al."Online multiple instance gradient feature selection for robust visual tracking".PATTERN RECOGNITION LETTERS 33.9(2012):1075-1082.

入库方式： OAI收割

来源：自动化研究所

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