dc.contributorGomes, Rafael Beserra
dc.contributor
dc.contributor
dc.contributorSouza, Anderson Abner de Santana
dc.contributor
dc.contributorSilva, Bruno Marques Ferreira da
dc.contributor
dc.contributorGonçalves, Luiz Marcos Garcia
dc.contributor
dc.contributorOliveira, Roberto Teodoro Gurgel de
dc.contributor
dc.creatorOliveira, Fábio Fonseca de
dc.date.accessioned2018-03-13T21:12:27Z
dc.date.accessioned2022-10-06T12:38:55Z
dc.date.available2018-03-13T21:12:27Z
dc.date.available2022-10-06T12:38:55Z
dc.date.created2018-03-13T21:12:27Z
dc.date.issued2017-07-03
dc.identifierOLIVEIRA, Fábio Fonseca de. Reconhecimento eficiente de objetos usando multifoveamento em nuvem de pontos 3D. 2017. 111f. Dissertação (Mestrado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2017.
dc.identifierhttps://repositorio.ufrn.br/jspui/handle/123456789/24830
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3956429
dc.description.abstractTechnological innovations in the field of hardware and 3D sensors allowed real time 3D point clouds acquisition. Therefore, varieties of interactive applications related to the 3D world that have been receiving increasing attention from researchers, arisen. However, one of the main problems that remains is the computationally intensive processing that requires optimized approaches to deal with this 3D vision model, especially when it is necessary to perform tasks in real time. Thus, we started from a proposed 3D multiresolution model presented as foveated point clouds which is a possible solution to this problem, but is limited to a single foveated structure with context dependent mobility. In this way, our proposal is an improvement of this model with the incorporation of multiple foveated structures. However, the union of several foveated structures results in a considerable increase of processing, since there are intersections between regions of distinct structures, which are processed multiple times. We address this problem by using a proposed multifoveated model that regards intersections on the union procedure. Such approach can be used to identify objects in 3D point clouds, one of the key tasks for automation, with efficient synchronization, allowing the validation of the model and verification of its applicability in the context of computer vision. The results demonstrate a gain in performance of the proposed model in relation to the use of multiple structures of the foveated point cloud model.
dc.publisherBrasil
dc.publisherUFRN
dc.publisherPROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO
dc.rightsAcesso Aberto
dc.subjectEstrutura foveada
dc.subjectMultifoveamento
dc.subjectReconhecimento de objetos 3D
dc.subjectNuvem de pontos
dc.subjectNuvens de pontos foveada
dc.titleReconhecimento eficiente de objetos usando multifoveamento em nuvem de pontos 3D
dc.typemasterThesis


Este ítem pertenece a la siguiente institución