Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/46784
Campo DC Valoridioma
dc.contributor.authorSánchez-Nielsen, Elenaen_US
dc.contributor.authorHernández Tejera, Marioen_US
dc.date.accessioned2018-11-23T08:08:59Z-
dc.date.available2018-11-23T08:08:59Z-
dc.date.issued2005en_US
dc.identifier.issn1045-0823en_US
dc.identifier.urihttp://hdl.handle.net/10553/46784-
dc.description.abstractFast and accurate tracking of moving objects in video streams is a critical process in computer vision. This problem can be formulated as exploration problems and thus can be expressed as a search into a state space based representation approach. However, these search problems are hard to solve because they involve search through a high dimensional space. In this paper, we describe an A*heuristic search for computing efficient search through a space of transformations corresponding to the 2D motion of the object, where most promising search alternatives are computed by means of integrating target dynamics into the search process, and ideas from information theory are used to guide the search. The paper includes evaluations with video streams that illustrate the efficiency and suitability for real-time vision tasks on general purpose hardware. Moreover, the computational cost to carry out the tracking task is smaller than real time requirements (40 ms).en_US
dc.languageengen_US
dc.sourceIJCAI International Joint Conference on Artificial Intelligence [ISSN 1045-0823], p. 1736-1737en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.titleAn heuristic search based approach for moving objects trackingen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.identifier.scopus34547521335-
dc.identifier.isi000290233000339-
dc.contributor.authorscopusid13105159100-
dc.contributor.authorscopusid55966875800-
dc.description.lastpage1737-
dc.description.firstpage1736-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
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-
Colección:Actas de congresos
Vista resumida

Citas SCOPUSTM   

2
actualizado el 21-abr-2024

Citas de WEB OF SCIENCETM
Citations

1
actualizado el 25-feb-2024

Visitas

31
actualizado el 22-jul-2023

Google ScholarTM

Verifica


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.