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hal.structure.identifier
dc.contributor.authorGouet-Brunet, Valérie
HAL ID: 170517
ORCID: 0000-0003-3666-5146
*
hal.structure.identifier
dc.contributor.authorHoang, Nguyen Vu*
hal.structure.identifier
dc.contributor.authorRukoz, Marta*
dc.date.accessioned2017-01-11T15:37:18Z
dc.date.available2017-01-11T15:37:18Z
dc.date.issued2013
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16150
dc.language.isoenen
dc.subjectCBIR
dc.subjectsymbolic images
dc.subjectknowledge graph
dc.subjectlocalization
dc.subjectobject detection
dc.subjectsimilarity search
dc.subjectspatial relationships
dc.subject.ddc005.7en
dc.titleObject detection and localization using a knowledge graph on spatial relationships
dc.typeCommunication / Conférence
dc.description.abstractenA knowledge on spatial relationships between objects present in a given collection of images can provide interesting information to improve classical CBIR tasks such as object detection and localization, by reducing the searching areas of the object relatively to one or several given objects. In this paper, we propose a representation of the knowledge on relationships existing between symbolic objects in a collection of images. None exhaustively, these relationships can be co-occurrences of objects or different kinds of spatial relationships between them in images. We present a graph-based representation of this knowledge and its associated operations and properties. This work was evaluated on the public symbolic image database LabelMe. The experiments show its relevance for object detection and localization.
dc.identifier.citationpages1-6
dc.relation.ispartoftitle2013 IEEE International Conference on Multimedia and Expo (ICME)
dc.relation.ispartofeditorA. El-Saddik, H. Wang, G. Su
dc.relation.ispartofpublnameIEEE
dc.relation.ispartofpublcityPiscataway, NJ
dc.relation.ispartofdate2013
dc.subject.ddclabelOrganisation des donnéesen
dc.relation.ispartofisbn978-1-4799-0015-2
dc.relation.confcountryUNITED STATES
dc.relation.forthcomingnonen
dc.identifier.doi10.1109/ICME.2013.6607602
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-02-08T15:24:57Z
hal.identifierhal-01432374*
hal.version1*
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hal.update.actionupdateFiles*
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