Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46783
DC FieldValueLanguage
dc.contributor.authorAntón-Canalís, Luisen_US
dc.contributor.authorHernández Tejera, Marioen_US
dc.contributor.authorSánchez-Nielsen, Elenaen_US
dc.date.accessioned2018-11-23T08:08:17Z-
dc.date.available2018-11-23T08:08:17Z-
dc.date.issued2006en_US
dc.identifier.isbn0-7695-2528-8en_US
dc.identifier.issn2164-7143en_US
dc.identifier.urihttp://hdl.handle.net/10553/46783-
dc.description.abstractA solution based on a swarm intelligence metaphor with a prey-predator scheme is proposed for real time object tracking in video sequences, which is a basic process in multiple computer vision tasks. Swarm predator particles fly on a Boid-like fashion over image prey pixels, using combined image features to guide individual movement rules. Object tracking emerges from interaction between predator particles and their environment. The paper includes method's description and experimental evaluations on video streams that illustrate the efficiency of swarm based methods in different vision tasks.en_US
dc.languageengen_US
dc.relationTecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccionen_US
dc.sourceProceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications, v. 2 (4021732), p. 604-609en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.titleParticle swarms as video sequence inhabitants for object tracking in computer visionen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.relation.conference6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)
dc.identifier.doi10.1109/ISDA.2006.253905en_US
dc.identifier.scopus34547494017-
dc.identifier.isi000242508100111-
dc.contributor.authorscopusid8921191600-
dc.contributor.authorscopusid55966875800-
dc.contributor.authorscopusid13105159100-
dc.identifier.eissn2164-7151-
dc.description.lastpage609-
dc.identifier.issue4021732-
dc.description.firstpage604-
dc.relation.volume2-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid3547239
dc.contributor.daisngid2188888
dc.contributor.daisngid1518383
dc.contributor.wosstandardWOS:Anton-Canalis, L
dc.contributor.wosstandardWOS:Hernandez-Tejera, M
dc.contributor.wosstandardWOS:Sanchez-Nielsen, E
dc.date.coverdate2006
dc.identifier.conferenceidevents120532
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.project.principalinvestigatorLorenzo Navarro, José Javier-
crisitem.event.eventsstartdate16-10-2006-
crisitem.event.eventsenddate18-10-2006-
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.fullNameHernández Tejera, Francisco Mario-
Appears in Collections:Actas de congresos
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