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Article: Median filtering-based methods for static background extraction from surveillance video

TitleMedian filtering-based methods for static background extraction from surveillance video
Authors
KeywordsAlternating direction method of multipliers
Video surveillance
Background extraction
Median filter
Singular value decomposition
Issue Date2015
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 Identifierhttp://hdl.handle.net/10722/251121
ISSN
2023 Impact Factor: 1.8
2023 SCImago Journal Rankings: 0.932
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xinxin-
dc.contributor.authorNg, Michael K.-
dc.contributor.authorYuan, Xiaoming-
dc.date.accessioned2018-02-01T01:54:39Z-
dc.date.available2018-02-01T01:54:39Z-
dc.date.issued2015-
dc.identifier.citationNumerical Linear Algebra with Applications, 2015, v. 22, n. 5, p. 845-865-
dc.identifier.issn1070-5325-
dc.identifier.urihttp://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.languageeng-
dc.relation.ispartofNumerical Linear Algebra with Applications-
dc.subjectAlternating direction method of multipliers-
dc.subjectVideo surveillance-
dc.subjectBackground extraction-
dc.subjectMedian filter-
dc.subjectSingular value decomposition-
dc.titleMedian filtering-based methods for static background extraction from surveillance video-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/nla.1981-
dc.identifier.scopuseid_2-s2.0-84940793225-
dc.identifier.volume22-
dc.identifier.issue5-
dc.identifier.spage845-
dc.identifier.epage865-
dc.identifier.eissn1099-1506-
dc.identifier.isiWOS:000360768900005-
dc.identifier.issnl1070-5325-

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