Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition
文献类型：期刊论文
| 作者 | Hu, Wenrui ; Yang, Yehui; Zhang, Wensheng; Xie, Yuan
|
| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| 出版日期 | 2017-02-01 |
| 卷号 | 26期号:2页码:724-737 |
| 关键词 | Moving Object Detection Tensor Nuclear Norm Tensor Total Variation Space-time Visual Saliency |
| DOI | 10.1109/TIP.2016.2627803 |
| 文献子类 | Article |
| 英文摘要 | In this paper, we propose a new low-rank and sparse representation model for moving object detection. The model preserves the natural space-time structure of video sequences by representing them as three-way tensors. Then, it operates the low-rank background and sparse foreground decomposition in the tensor framework. On the one hand, we use the tensor nuclear norm to exploit the spatio-temporal redundancy of background based on the circulant algebra. On the other, we use the new designed saliently fused-sparse regularizer (SFS) to adaptively constrain the foreground with spatio-temporal smoothness. To refine the existing foreground smooth regularizers, the SFS incorporates the local spatio-temporal geometric structure information into the tensor total variation by using the 3D locally adaptive regression kernel (3D-LARK). What is more, the SFS further uses the 3D-LARK to compute the space-time motion saliency of foreground, which is combined with the l(1) norm and improves the robustness of foreground extraction. Finally, we solve the proposed model with globally optimal guarantee. Extensive experiments on challenging well-known data sets demonstrate that our method significantly outperforms the state-of-the-art approaches and works effectively on a wide range of complex scenarios. |
| WOS关键词 | BACKGROUND SUBTRACTION ; VISUAL SURVEILLANCE ; REGULARIZATION ; FRAMEWORK ; RECOVERY ; ROBUST ; IMAGE |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000404773100010 |
| 资助机构 | National Natural Science Foundation of China(61402480 ; 61432008 ; 61472423 ; 61502495 ; 61532006) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15244]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Wenrui,Yang, Yehui,Zhang, Wensheng,et al. Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2017,26(2):724-737. |
| APA | Hu, Wenrui,Yang, Yehui,Zhang, Wensheng,&Xie, Yuan.(2017).Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition.IEEE TRANSACTIONS ON IMAGE PROCESSING,26(2),724-737. |
| MLA | Hu, Wenrui,et al."Moving Object Detection Using Tensor-Based Low-Rank and Saliently Fused-Sparse Decomposition".IEEE TRANSACTIONS ON IMAGE PROCESSING 26.2(2017):724-737. |
入库方式： OAI收割
来源：自动化研究所
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