SIA OpenIR  > 机器人学研究室
Video Desnowing and Deraining Based on Matrix Decomposition
Ren WH(任卫红); Tian JD(田建东); Han Z(韩志); Chan, Antoni; Tang YD(唐延东)
Department机器人学研究室
Conference Name30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017)
Conference DateJuly 21-26, 2017
Conference PlaceHonolulu, USA
Source Publication30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017)
PublisherIEEE
Publication PlaceNew York
2017
Pages2838-2847
Indexed ByEI ; CPCI(ISTP)
EI Accession number20181304952985
WOS IDWOS:000418371402095
Contribution Rank1
ISSN1063-6919
ISBN978-1-5386-0457-1
Abstract

The existing snow/rain removal methods often fail for heavy snow/rain and dynamic scene. One reason for the failure is due to the assumption that all the snowflakes/rain streaks are sparse in snow/rain scenes. The other is that the existing methods often can not differentiate moving objects and snowflakes/rain streaks. In this paper, we propose a model based on matrix decomposition for video desnowing and deraining to solve the problems mentioned above. We divide snowflakes/rain streaks into two categories: sparse ones and dense ones. With background fluctuations and optical flow information, the detection of moving objects and sparse snowflakes/rain streaks is formulated as a multi-label Markov Random Fields (MRFs). As for dense snowflakes/rain streaks, they are considered to obey Gaussian distribution. The snowflakes/rain streaks, including sparse ones and dense ones, in scene backgrounds are removed by low-rank representation of the backgrounds. Meanwhile, a group sparsity term in our model is designed to filter snow/rain pixels within the moving objects. Experimental results show that our proposed model performs better than the state-of-the-art methods for snow and rain removal.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21359
Collection机器人学研究室
Corresponding AuthorTian JD(田建东)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.City University of Hong Kong
Recommended Citation
GB/T 7714
Ren WH,Tian JD,Han Z,et al. Video Desnowing and Deraining Based on Matrix Decomposition[C]. New York:IEEE,2017:2838-2847.
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