Challenging situations for background subtraction algorithms

dc.contributor.authorSanches, Silvio R. R.
dc.contributor.authorOliveira, Claiton
dc.contributor.authorSementille, Antonio C. [UNESP]
dc.contributor.authorFreire, Valdinei
dc.contributor.institutionUniv Tecnol Fed Parana
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2019-10-04T12:13:38Z
dc.date.available2019-10-04T12:13:38Z
dc.date.issued2019-05-01
dc.description.abstractBackground subtraction is the prerequisite for a wide range of applications including video surveillance, smart environments and content retrieval. Real environments present some challenging situations even for the most recent algorithms, such as shadows, illumination changes, dynamic background, among others. If a real environment is previously known and the challenging situations of this environment can be predicted, the choice of an appropriate algorithm to deal with such situations may be essential for obtaining better segmentation results. In our work, we identify the main situations that affect the performance of background subtraction algorithms and present a classification of these challenging situations. In addition, we present a solution that uses videos and ground-truths from existing datasets to evaluate the performance of segmentation algorithms when they need to deal with a specific challenging situation.en
dc.description.affiliationUniv Tecnol Fed Parana, Cornelio Procopio, PR, Brazil
dc.description.affiliationUniv Estadual Paulista, Bauru, Brazil
dc.description.affiliationUniv Sao Paulo, Sao Paulo, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Bauru, Brazil
dc.format.extent1771-1784
dc.identifierhttp://dx.doi.org/10.1007/s10489-018-1346-4
dc.identifier.citationApplied Intelligence. Dordrecht: Springer, v. 49, n. 5, p. 1771-1784, 2019.
dc.identifier.doi10.1007/s10489-018-1346-4
dc.identifier.issn0924-669X
dc.identifier.urihttp://hdl.handle.net/11449/184438
dc.identifier.wosWOS:000463843400009
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofApplied Intelligence
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectBackground subtraction
dc.subjectForeground extraction
dc.subjectAlgorithm evaluation
dc.subjectChallenging situation
dc.titleChallenging situations for background subtraction algorithmsen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer
unesp.author.lattes1882712230914196[3]
unesp.author.orcid0000-0002-4337-514X[3]

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