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Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking

文献类型：期刊论文

作者Hu, Weiming1; Li, Xi1; Zhang, Xiaoqin2; Shi, Xinchu1; Maybank, Stephen3; Zhang, Zhongfei4
刊名INTERNATIONAL JOURNAL OF COMPUTER VISION
出版日期2011-02-01
卷号91期号:3页码:303-327
关键词Incremental learning Tensor subspace Foreground segmentation Tracking
英文摘要Appearance modeling is very important for background modeling and object tracking. Subspace learning-based algorithms have been used to model the appearances of objects or scenes. Current vector subspace-based algorithms cannot effectively represent spatial correlations between pixel values. Current tensor subspace-based algorithms construct an offline representation of image ensembles, and current online tensor subspace learning algorithms cannot be applied to background modeling and object tracking. In this paper, we propose an online tensor subspace learning algorithm which models appearance changes by incrementally learning a tensor subspace representation through adaptively updating the sample mean and an eigenbasis for each unfolding matrix of the tensor. The proposed incremental tensor subspace learning algorithm is applied to foreground segmentation and object tracking for grayscale and color image sequences. The new background models capture the intrinsic spatiotemporal characteristics of scenes. The new tracking algorithm captures the appearance characteristics of an object during tracking and uses a particle filter to estimate the optimal object state. Experimental evaluations against state-of-the-art algorithms demonstrate the promise and effectiveness of the proposed incremental tensor subspace learning algorithm, and its applications to foreground segmentation and object tracking.
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]ROBUST VISUAL TRACKING ; SHADOW SEGMENTATION ; APPEARANCE MODELS ; REPRESENTATION ; SURVEILLANCE ; RECOGNITION ; PEOPLE ; OBJECT ; CUES
收录类别SCI
语种英语
WOS记录号WOS:000286610300005
源URL[http://ir.ia.ac.cn/handle/173211/3248]  
专题自动化研究所_模式识别国家重点实验室_视频内容安全团队
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Wenzhou Univ, Coll Math & Informat Sci, Wenzhou 325000, Zhejiang, Peoples R China
3.Univ London Birkbeck Coll, Dept Comp Sci & Informat Syst, London WC1E 7HX, England
4.SUNY Binghamton, Binghamton, NY 13902 USA
推荐引用方式
GB/T 7714		 Hu, Weiming,Li, Xi,Zhang, Xiaoqin,et al. Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2011,91(3):303-327.
APA Hu, Weiming,Li, Xi,Zhang, Xiaoqin,Shi, Xinchu,Maybank, Stephen,&Zhang, Zhongfei.(2011).Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking.INTERNATIONAL JOURNAL OF COMPUTER VISION,91(3),303-327.
MLA Hu, Weiming,et al."Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking".INTERNATIONAL JOURNAL OF COMPUTER VISION 91.3(2011):303-327.

入库方式： OAI收割

来源：自动化研究所

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