Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/46782
Campo DC | Valor | idioma |
---|---|---|
dc.contributor.author | Antón Canalís,Luis | en_US |
dc.contributor.author | Sánchez-Nielsen, Elena | en_US |
dc.contributor.author | Hernández Tejera, Mario | en_US |
dc.date.accessioned | 2018-11-23T08:07:35Z | - |
dc.date.available | 2018-11-23T08:07:35Z | - |
dc.date.issued | 2006 | en_US |
dc.identifier.isbn | 978-972-8865-40-5 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/46782 | - |
dc.description.abstract | A 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.language | eng | en_US |
dc.relation | Tecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccion | en_US |
dc.source | VISAPP 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. 221-228 | en_US |
dc.subject | 1203 Ciencia de los ordenadores | en_US |
dc.subject.other | Computer vision | en_US |
dc.subject.other | Real time object tracking | en_US |
dc.subject.other | Swarm intelligence | en_US |
dc.title | Swarmtrack: a particle swarm approach to visual tracking | en_US |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.type | ConferenceObject | es |
dc.identifier.scopus | 55749110295 | - |
dc.identifier.isi | 000241914300035 | - |
dc.contributor.authorscopusid | 8921191600 | - |
dc.contributor.authorscopusid | 13105159100 | - |
dc.contributor.authorscopusid | 55966875800 | - |
dc.description.lastpage | 228 | - |
dc.description.firstpage | 221 | - |
dc.relation.volume | 2 | - |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Actas de congresos | en_US |
dc.identifier.ulpgc | Sí | es |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.project.principalinvestigator | Lorenzo Navarro, José Javier | - |
crisitem.author.dept | GIR SIANI: Inteligencia Artificial, Redes Neuronales, Aprendizaje Automático e Ingeniería de Datos | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.orcid | 0000-0001-9717-8048 | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.fullName | Antón Canalís, Luis | - |
crisitem.author.fullName | Hernández Tejera, Francisco Mario | - |
Colección: | Actas de congresos |
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