Tensor RPCA by Bayesian CP Factorization with Complex Noise
文献类型：会议论文
| 作者 | Chen XA(陈希爱) ; Luo Q(罗琼); Liang D(梁栋); Meng DY(孟德宇); Wang Y(王尧); Han Z(韩志); Tang YD(唐延东)
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| 出版日期 | 2017 |
| 会议名称 | 2017 IEEE International Conference on Computer Vision (ICCV) |
| 会议日期 | October 22-29, 2017 |
| 会议地点 | Venice, Italy |
| 页码 | 5029-5038 |
| 通讯作者 | Han Z(韩志) |
| 中文摘要 | The RPCA model has achieved good performances in various applications. However, two defects limit its effectiveness. Firstly, it is designed for dealing with data in matrix form, which fails to exploit the structure information of higher order tensor data in some pratical situations. Secondly, it adopts L1-norm to tackle noise part which makes it only valid for sparse noise. In this paper, we propose a tensor RPCA model based on CP decomposition and model data noise by Mixture of Gaussians (MoG). The use of tensor structure to raw data allows us to make full use of the inherent structure priors, and MoG is a general approximator to any blends of consecutive distributions, which makes our approach capable of regaining the low dimensional linear subspace from a wide range of noises or their mixture. The model is solved by a new proposed algorithm inferred under a variational Bayesian framework. The superiority of our approach over the existing state-of-the-art approaches is demonstrated by extensive experiments on both of synthetic and real data. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2017 IEEE International Conference on Computer Vision (ICCV)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISSN号 | 2380-7504 |
| ISBN号 | 978-1-5386-1032-9 |
| WOS记录号 | WOS:000425498405012 |
| 源URL | [http://ir.sia.cn/handle/173321/21357]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China 2.Xi'An Jiaotong University, China 3.University of Chinese Academy of Sciences, China |
| 推荐引用方式 GB/T 7714 | Chen XA,Luo Q,Liang D,et al. Tensor RPCA by Bayesian CP Factorization with Complex Noise[C]. 见:2017 IEEE International Conference on Computer Vision (ICCV). Venice, Italy. October 22-29, 2017. |
入库方式： OAI收割
来源：沈阳自动化研究所
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