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Article: Median filtering-based methods for static background extraction from surveillance video
Title | Median filtering-based methods for static background extraction from surveillance video |
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Authors | |
Keywords | Alternating direction method of multipliers Video surveillance Background extraction Median filter Singular value decomposition |
Issue Date | 2015 |
Citation | Numerical Linear Algebra with Applications, 2015, v. 22, n. 5, p. 845-865 How to Cite? |
Abstract | © 2015 John Wiley & Sons, Ltd. We propose some computational methods for extracting static backgrounds from surveillance videos corrupted by noise, blur, or both. The new methods are constructed based on the fact that the matrix representation of a static background consists of identical columns; hence the idea of median filtering is embedded in these methods. These new methods significantly differ from existing methods originating from the robust principal component analysis (RPCA) in that no nuclear-norm term is involved; thus the computation of singular value decomposition can be completely avoided when solving these new models iteratively. This is an important feature because usually the dimensionality of a surveillance video is large and so the involved singular value decomposition (which is inevitable for RPCA-based models) is very expensive computationally. We show that these methods can be easily solved by well-developed operator splitting methods in optimization literature such as the alternating direction method of multipliers. We compare the new methods with their RPCA-based counterparts via testing some synthetic and real videos. Our numerical results show that compared with RPCA-based models, these median filtering-based vaiational models can extract more accurate backgrounds when the background in a surveillance video is static, and numerically, they can be solved much more efficiently. |
Persistent Identifier | http://hdl.handle.net/10722/251121 |
ISSN | 2023 Impact Factor: 1.8 2023 SCImago Journal Rankings: 0.932 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Xinxin | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Yuan, Xiaoming | - |
dc.date.accessioned | 2018-02-01T01:54:39Z | - |
dc.date.available | 2018-02-01T01:54:39Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Numerical Linear Algebra with Applications, 2015, v. 22, n. 5, p. 845-865 | - |
dc.identifier.issn | 1070-5325 | - |
dc.identifier.uri | http://hdl.handle.net/10722/251121 | - |
dc.description.abstract | © 2015 John Wiley & Sons, Ltd. We propose some computational methods for extracting static backgrounds from surveillance videos corrupted by noise, blur, or both. The new methods are constructed based on the fact that the matrix representation of a static background consists of identical columns; hence the idea of median filtering is embedded in these methods. These new methods significantly differ from existing methods originating from the robust principal component analysis (RPCA) in that no nuclear-norm term is involved; thus the computation of singular value decomposition can be completely avoided when solving these new models iteratively. This is an important feature because usually the dimensionality of a surveillance video is large and so the involved singular value decomposition (which is inevitable for RPCA-based models) is very expensive computationally. We show that these methods can be easily solved by well-developed operator splitting methods in optimization literature such as the alternating direction method of multipliers. We compare the new methods with their RPCA-based counterparts via testing some synthetic and real videos. Our numerical results show that compared with RPCA-based models, these median filtering-based vaiational models can extract more accurate backgrounds when the background in a surveillance video is static, and numerically, they can be solved much more efficiently. | - |
dc.language | eng | - |
dc.relation.ispartof | Numerical Linear Algebra with Applications | - |
dc.subject | Alternating direction method of multipliers | - |
dc.subject | Video surveillance | - |
dc.subject | Background extraction | - |
dc.subject | Median filter | - |
dc.subject | Singular value decomposition | - |
dc.title | Median filtering-based methods for static background extraction from surveillance video | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1002/nla.1981 | - |
dc.identifier.scopus | eid_2-s2.0-84940793225 | - |
dc.identifier.volume | 22 | - |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 845 | - |
dc.identifier.epage | 865 | - |
dc.identifier.eissn | 1099-1506 | - |
dc.identifier.isi | WOS:000360768900005 | - |
dc.identifier.issnl | 1070-5325 | - |