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Please use this identifier to cite or link to this item: https://accedacris.ulpgc.es/jspui/handle/10553/17531
DC FieldValueLanguage
dc.contributor.authorCastrillón-Santana, M.en_US
dc.contributor.authorVuong, Quoc C.en_US
dc.contributor.otherCastrillon-Santana, Modesto-
dc.contributor.otherVuong, Quoc-
dc.date.accessioned2016-06-21T08:59:58Z-
dc.date.accessioned2018-06-15T09:25:30Z-
dc.date.available2016-06-21T08:59:58Z-
dc.date.available2018-06-15T09:25:30Z-
dc.date.issued2006en_US
dc.identifier.isbn3-540-45914-6en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttps://accedacris.ulpgc.es/handle/10553/17531-
dc.description.abstractAutomatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automatic vision systems for pedestrian detection be improved by training them on perceptually-defined ROIs?en_US
dc.languageengen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [ISSN 0302-9743], v. 4177 LNAI, p. 163-170en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherHead Trackingen_US
dc.titleCombining human perception and geometric restrictions for automatic pedestrian detectionen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference11th Conference of the Spanish-Association-for-Artificial-Intelligenceen_US
dc.identifier.doi10.1007/1188216_18en_US
dc.identifier.scopus33750260721-
dc.identifier.isi000242119100018-
dcterms.isPartOfCurrent Topics In Artificial Intelligence-
dcterms.sourceCurrent Topics In Artificial Intelligence[ISSN 0302-9743],v. 4177, p. 163-170-
dc.contributor.authorscopusid22333278500-
dc.contributor.authorscopusid6603878019-
dc.identifier.absysnet725932-
dc.description.lastpage170en_US
dc.description.firstpage163en_US
dc.relation.volume4177 LNAIen_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.project.referenceTIN2004-07087es
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.type2Actas de congresosen_US
dc.identifier.wosWOS:000242119100018-
dc.contributor.daisngid1060138-
dc.contributor.daisngid32145428-
dc.contributor.daisngid555067-
dc.identifier.investigatorRIDK-9040-2014-
dc.identifier.investigatorRIDNo ID-
dc.utils.revisionSíen_US
dc.contributor.wosstandardWOS:Castrillon-Santana, M-
dc.contributor.wosstandardWOS:Vuong, QC-
dc.date.coverdateEnero 2006en_US
dc.identifier.conferenceidevents120529-
dc.identifier.ulpgcSíen_US
dc.contributor.buulpgcBU-INFen_US
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.event.eventsstartdate16-11-2005-
crisitem.event.eventsenddate18-11-2005-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional-
crisitem.author.deptIU de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-8673-2725-
crisitem.author.parentorgIU de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería-
crisitem.author.fullNameCastrillón Santana, Modesto Fernando-
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