1. DIGITAL.CSIC
  2. Ciencia y Tecnologías Físicas
  3. Instituto de Investigación en Inteligencia Artificial (IIIA)
  4. (IIIA) Comunicaciones congresos
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/9510
COMPARTIR / EXPORTAR:
logo share SHARE logo core CORE BASE

Comparte tu historia
de Acceso Abierto
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Campo DC Valor Lengua/Idioma
dc.contributor.authorRibes, Arturo-
dc.contributor.authorRamisa, Arnau-
dc.contributor.authorLópez de Mántaras, Ramón-
dc.contributor.authorToledo, Ricardo-
dc.date.accessioned2009-01-09T12:37:24Z-
dc.date.available2009-01-09T12:37:24Z-
dc.date.issued2008-
dc.identifier.citationArtificial Intelligence Research and Development, Proceedings of the 11 th International Conference of the Catalan Association for Artificial Intelligence, (CCIA 2008), Sant Marti d'Empuries, Girona, October 22-24. Frontiers in Artificial Intelligence and Applications, IOS Press Vol. 184 (2008) pp. 388-397.en_US
dc.identifier.isbn978-1-58603-925-7-
dc.identifier.issn0922-6389-
dc.identifier.urihttp://hdl.handle.net/10261/9510-
dc.descriptionThe original publication is available at http://www.booksonline.iospress.nl/Content/View.aspx?piid=10600en_US
dc.description.abstractObject recognition has been widely researched for several decades and in the recent years new methods capable of general object classification have appeared. However very few work has been done to adapt these methods to the challenges raised by mobile robotics. In this article we discuss the data sources (appearence information, temporal context, etc.) that such methods could use and we review several state of the art object recognition methods that build in one or more of these sources. Finally we run an object based robot localization experiment using an state of the art object recognition method and we show that good results are obtained even with a naïve place descriptor.en_US
dc.description.sponsorshipThis work has been partially funded by the FI grant and the BE grant from the AGAUR, the 2005/SGR/00093 project, supported by the Generalitat de Catalunya , the MIDCBR project grant TIN 200615140C0301, TIN 200615308C0202 and FEDER funds.en_US
dc.format.extent1506236 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoengen_US
dc.publisherIOS Pressen_US
dc.rightsopenAccessen_US
dc.subjectArtificial intelligenceen_US
dc.subjectObject recognitionen_US
dc.subjectRobot localizationen_US
dc.subjectMobile robotsen_US
dc.titleObject-based Place Recognition for Mobile Robots Using Panoramasen_US
dc.typeartículoen_US
dc.identifier.doi10.3233/978-1-58603-925-7-388-
dc.description.peerreviewedPeer revieweden_US
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeartículo-
item.cerifentitytypePublications-
item.grantfulltextopen-
Aparece en las colecciones: (IIIA) Comunicaciones congresos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato
CCIA08_FAIA_184.pdf1,47 MBAdobe PDFVista previa
Visualizar/Abrir
Show simple item record

CORE Recommender

SCOPUSTM   
Citations

1
checked on 18-abr-2024

WEB OF SCIENCETM
Citations

1
checked on 28-feb-2024

Page view(s)

389
checked on 22-abr-2024

Download(s)

139
checked on 22-abr-2024

Google ScholarTM

Check

Altmetric

Altmetric


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.