Single and Multiple Object Tracking Using Log-Euclidean Riemannian Subspace and Block-Division Appearance Model
文献类型：期刊论文
| 作者 | Hu, Weiming1 ; Li, Xi1; Luo, Wenhan1; Zhang, Xiaoqin1; Maybank, Stephen2; Zhang, Zhongfei3
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| 刊名 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 |
| 出版日期 | 2012-12-01 |
| 卷号 | 34期号:12页码:2420-2440 |
| 关键词 | Visual object tracking occlusion reasoning log-euclidean Riemannian subspace incremental learning block-division appearance model |
| 英文摘要 | Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | VISUAL TRACKING ; PEOPLE ; RECOGNITION ; SCENE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000309913700011 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3275]  |
| 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.Univ London Birkbeck Coll, Dept Comp Sci & Informat Syst, London WC1E 7HX, England 3.SUNY Binghamton, Watson Sch Engn & Appl Sci, Dept Comp Sci, Binghamton, NY 13902 USA |
| 推荐引用方式 GB/T 7714 | Hu, Weiming,Li, Xi,Luo, Wenhan,et al. Single and Multiple Object Tracking Using Log-Euclidean Riemannian Subspace and Block-Division Appearance Model[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2012,34(12):2420-2440. |
| APA | Hu, Weiming,Li, Xi,Luo, Wenhan,Zhang, Xiaoqin,Maybank, Stephen,&Zhang, Zhongfei.(2012).Single and Multiple Object Tracking Using Log-Euclidean Riemannian Subspace and Block-Division Appearance Model.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,34(12),2420-2440. |
| MLA | Hu, Weiming,et al."Single and Multiple Object Tracking Using Log-Euclidean Riemannian Subspace and Block-Division Appearance Model".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 34.12(2012):2420-2440. |
入库方式： OAI收割
来源：自动化研究所
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