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dc.contributor.authorPicos, Kenia-
dc.contributor.authorOrozco Rosas, Ulises-
dc.date.accessioned2020-08-05T18:41:54Z-
dc.date.available2020-08-05T18:41:54Z-
dc.date.created2019-07-
dc.date.issued2021-05-
dc.identifier.urihttps://repositorio.cetys.mx/handle/60000/813-
dc.description.abstractAn accurate method based on evolutionary correlation filtering to solve pose estimation of highly occluded targets is presented. The proposed method performs multiple correlation operations between an input scene and a bank of filters designed in frequency-domain. Each filter is computed with statistical parameters of a real-world scene and a template that contains information of the target in a single pose parameter configuration. A vast set of templates is generated from multiple views of a three-dimensional model of the target, which are created synthetically with computer graphics. An evolutionary approach in the bank of filter construction for optimizing the pose estimation parameters is implemented. The evolutionary computation technique based on a pseudo-bacterial genetic algorithm yields high estimation accuracy finding the best filter that produces the highest matching score. The proposed evolutionary correlation filtering yields good convergence of the bank of filter optimization, which produces a reduction of the number of computational operations. Experimental results demonstrate the robustness of the proposed method in terms of detection performance and pose estimation of highly occluded targets compared with state-of-the-art methods.es_ES
dc.language.isoen_USes_ES
dc.rightsAtribución-NoComercial-CompartirIgual 2.5 México*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/2.5/mx/*
dc.subjectPose estimationes_ES
dc.subjectEvolutionary correlation filteringes_ES
dc.subjectTemplate match filterses_ES
dc.subjectThree-dimensional posees_ES
dc.titleEvolutionary correlation filtering based on pseudobacterial genetic algorithm for pose estimation of highly occluded targetses_ES
dc.title.alternativeMultimedia Tools and Applicationses_ES
dc.typeArticlees_ES
dc.identifier.doihttps://doi.org/10.1007/s11042-020-08991-7-
dc.identifier.indexacionSCOPUS / JCRes_ES
dc.subject.sedeCampus Ensenadaes_ES
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