Background Reconstruction via Low Rank Tensor Factorization
文献类型：会议论文
| 作者 | Zhang Y(张杨)1,2,3; Tang YD(唐延东)2,3 ; Chen XA(陈希爱)1,2,3; Han Z(韩志)2,3; Shen GP(沈贵萍)1,2,3
|
| 出版日期 | 2018 |
| 会议日期 | December 12-14, 2018 |
| 会议地点 | Chengdu, China |
| 关键词 | background reconstruction low rank Tensor factorization MoG MRF |
| 页码 | 1-7 |
| 英文摘要 | This paper introduces a new method for background reconstruction. Background reconstruction from video sequences captured by a static camera can be regarded as a low rank factorization problem. Background is the low dimensional subspace restored from the higher dimensional visual data, and foreground is treated as sparse noise of unknown distribution. The existing algorithm could not deal with noise of unknown distribution effectively. Due to the limitation of the matrix decomposition which would lost space structure information, we process video data directly as higher order tensor based on low rank tensor factorization (LRTF). We put forward a new model of foreground by using Mixture of Gaussians (MoG) and Markov Random Field (MRF). Extensive experiments show that our method can effectively construct the background. |
| 产权排序 | 1 |
| 会议录 | 2018 10th International Conference on Graphics and Image Processing (ICGIP 2018)
 |
| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-2828-1 |
| WOS记录号 | WOS:000485096200010 |
| 源URL | [http://ir.sia.cn/handle/173321/23845]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Shen GP(沈贵萍) |
| 作者单位 | 1.University of Chinese Academy of Sciences, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China |
| 推荐引用方式 GB/T 7714 | Zhang Y,Tang YD,Chen XA,et al. Background Reconstruction via Low Rank Tensor Factorization[C]. 见:. Chengdu, China. December 12-14, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。