Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/46782
DC Field | Value | Language |
---|---|---|
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 | - |
Appears in Collections: | Actas de congresos |
SCOPUSTM
Citations
10
checked on Nov 17, 2024
WEB OF SCIENCETM
Citations
2
checked on Feb 25, 2024
Page view(s)
90
checked on Jun 15, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.