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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/70830
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dc.contributor.authorAraujo, Ernesto-
dc.contributor.authorSilva, Cassiano R.-
dc.contributor.authorSampaio, Daniel J.B.S.-
dc.date.accessioned2014-05-27T11:23:49Z-
dc.date.accessioned2016-10-25T18:26:37Z-
dc.date.available2014-05-27T11:23:49Z-
dc.date.available2016-10-25T18:26:37Z-
dc.date.issued2008-12-01-
dc.identifierhttp://www.wseas.us/e-library/transactions/signal/2008/28-145.pdf-
dc.identifier.citationWSEAS Transactions on Signal Processing, v. 4, n. 8, p. 420-431, 2008.-
dc.identifier.issn1790-5022-
dc.identifier.urihttp://hdl.handle.net/11449/70830-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/70830-
dc.description.abstractA target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.en
dc.format.extent420-431-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectComputational intelligence-
dc.subjectImage motion-
dc.subjectNeural network-
dc.subjectTarget tracking-
dc.subjectVideo digital camera-
dc.subjectArtificial intelligence-
dc.subjectCameras-
dc.subjectComputer graphics-
dc.subjectDigital cameras-
dc.subjectImage analysis-
dc.subjectImage enhancement-
dc.subjectIntelligent control-
dc.subjectLearning algorithms-
dc.subjectTargets-
dc.subjectTracking (position)-
dc.subjectVegetation-
dc.subjectVideo cameras-
dc.subjectColored images-
dc.subjectCompetitive learnings-
dc.subjectCompetitive neural networks-
dc.subjectDigital sequences-
dc.subjectMoving targets-
dc.subjectPre-processing-
dc.subjectReal times-
dc.subjectReal worlds-
dc.subjectSequence of images-
dc.subjectTracking algorithms-
dc.subjectVideo target tracking-
dc.subjectWinning neurons-
dc.subjectNeural networks-
dc.titleVideo target tracking by using competitive neural networksen
dc.typeoutro-
dc.contributor.institutionInstituto Nacional de Pesquisas Espaciais (INPE)-
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)-
dc.contributor.institutionHospital Municipal Dr. José de Carvalho Florence-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationIntegration and Testing Laboratory - LIT Space Technologies and Engineering - ETE Instituto Nacional de Pesquisas Espaciais - INPE, Av. Astronautas, 1758, 12.227-010 São José dos Campos-
dc.description.affiliationHealth Informatics Dept. - DIS Universidade Federal de São Paulo - UNIFESP, Botucatu, 862, 04023-062 São Paulo-
dc.description.affiliationHospital Municipal Dr. José de Carvalho Florence, Av. Saigiro Nakamura, 800, 04023-062 São José dos Campos-
dc.description.affiliationElectrical Engineering Department Universidade Estadual Paulista - UNESP, Av. Dr. Ariberto Pereira da Cunha, 333, 12.516-410 Guaratinguetá-
dc.description.affiliationUnespElectrical Engineering Department Universidade Estadual Paulista - UNESP, Av. Dr. Ariberto Pereira da Cunha, 333, 12.516-410 Guaratinguetá-
dc.rights.accessRightsAcesso aberto-
dc.relation.ispartofWSEAS Transactions on Signal Processing-
dc.identifier.scopus2-s2.0-58249104081-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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