Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46782
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dc.contributor.authorAntón Canalís,Luisen_US
dc.contributor.authorSánchez-Nielsen, Elenaen_US
dc.contributor.authorHernández Tejera, Marioen_US
dc.date.accessioned2018-11-23T08:07:35Z-
dc.date.available2018-11-23T08:07:35Z-
dc.date.issued2006en_US
dc.identifier.isbn978-972-8865-40-5en_US
dc.identifier.urihttp://hdl.handle.net/10553/46782-
dc.description.abstractA new approach to solve the object tracking problem is proposed using a Swarm Intelligence metaphor. It is based on a prey-predator scheme with a swarm of predator particles defined to track a herd of prey pixels using the intensity of its flavours. The method is described, including the definition of predator particles' behaviour as a set of rules in a Boids fashion. Object tracking behaviour emerges from the interaction of individual particles. The paper includes experimental evaluations with video streams that illustrate the robustness and efficiency for real-time vision based tasks using a general purpose computer.en_US
dc.languageengen_US
dc.relationTecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccionen_US
dc.sourceVISAPP 2006 - Proceedings of the 1st International Conference on Computer Vision Theory and Applications, february, 25-28, 2006, in Setúbal, Portugal [ISBN 972-8865-40-6], v. 2, p. 221-228en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.subject.otherComputer visionen_US
dc.subject.otherReal time object trackingen_US
dc.subject.otherSwarm intelligenceen_US
dc.titleSwarmtrack: a particle swarm approach to visual trackingen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.identifier.scopus55749110295-
dc.identifier.isi000241914300035-
dc.contributor.authorscopusid8921191600-
dc.contributor.authorscopusid13105159100-
dc.contributor.authorscopusid55966875800-
dc.description.lastpage228-
dc.description.firstpage221-
dc.relation.volume2-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.project.principalinvestigatorLorenzo Navarro, José Javier-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0001-9717-8048-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameAntón Canalís, Luis-
crisitem.author.fullNameHernández Tejera, Francisco Mario-
Appears in Collections:Actas de congresos
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