LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation
In scenes with dynamic background or measurement noise, the low-rank sparse decomposition background modeling algorithm based on kernel norm constraint is easy to separate the moving background or noise as part of the foreground and the foreground at the same time, and it has poor modeling performa...
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2021-11-01
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| Series: | EAI Endorsed Transactions on Scalable Information Systems |
| Subjects: | |
| Online Access: | https://publications.eai.eu/index.php/sis/article/view/302 |
| _version_ | 1798027599195144192 |
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| author | Hongqiao Gao |
| author_facet | Hongqiao Gao |
| author_sort | Hongqiao Gao |
| collection | DOAJ |
| description |
In scenes with dynamic background or measurement noise, the low-rank sparse decomposition background modeling algorithm based on kernel norm constraint is easy to separate the moving background or noise as part of the foreground and the foreground at the same time, and it has poor modeling performance for complex background. In order to solve this problem, this paper proposes a low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation. Firstly, low-rank sparse decomposition is used to constrain the background matrix. Secondly, the moving objects in the region of interest (ROI) are extracted by symmetrical frame difference method, and the background image is obtained by block background modeling. Numerical experiments show that compared with other five main algorithms, the proposed algorithm can separate moving objects more accurately in the scene with dynamic background.
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| first_indexed | 2024-04-11T18:54:03Z |
| format | Article |
| id | doaj.art-5f9a66262cca4f438202cc0cc093bed2 |
| institution | Directory Open Access Journal |
| issn | 2032-9407 |
| language | English |
| last_indexed | 2024-04-11T18:54:03Z |
| publishDate | 2021-11-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Scalable Information Systems |
| spelling | doaj.art-5f9a66262cca4f438202cc0cc093bed22022-12-22T04:08:15ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Scalable Information Systems2032-94072021-11-0193610.4108/eai.16-11-2021.172133LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separationHongqiao Gao0Luoyang Polytechnic In scenes with dynamic background or measurement noise, the low-rank sparse decomposition background modeling algorithm based on kernel norm constraint is easy to separate the moving background or noise as part of the foreground and the foreground at the same time, and it has poor modeling performance for complex background. In order to solve this problem, this paper proposes a low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation. Firstly, low-rank sparse decomposition is used to constrain the background matrix. Secondly, the moving objects in the region of interest (ROI) are extracted by symmetrical frame difference method, and the background image is obtained by block background modeling. Numerical experiments show that compared with other five main algorithms, the proposed algorithm can separate moving objects more accurately in the scene with dynamic background. https://publications.eai.eu/index.php/sis/article/view/302low-rank sparse decompositionsymmetrical frame differenceROI |
| spellingShingle | Hongqiao Gao LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation EAI Endorsed Transactions on Scalable Information Systems low-rank sparse decomposition symmetrical frame difference ROI |
| title | LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation |
| title_full | LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation |
| title_fullStr | LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation |
| title_full_unstemmed | LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation |
| title_short | LRSDSFD: low-rank sparse decomposition and symmetrical frame difference method for moving video foreground-background separation |
| title_sort | lrsdsfd low rank sparse decomposition and symmetrical frame difference method for moving video foreground background separation |
| topic | low-rank sparse decomposition symmetrical frame difference ROI |
| url | https://publications.eai.eu/index.php/sis/article/view/302 |
| work_keys_str_mv | AT hongqiaogao lrsdsfdlowranksparsedecompositionandsymmetricalframedifferencemethodformovingvideoforegroundbackgroundseparation |