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Contrast invariant features for human detection in far infrared images

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dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Sistemas Inteligenteses
dc.contributor.authorOlmeda Reino, Daniel
dc.contributor.authorEscalera Hueso, Arturo de la
dc.contributor.authorArmingol Moreno, José María
dc.date.accessioned2013-09-17T10:08:50Z
dc.date.available2013-09-17T10:08:50Z
dc.date.issued2012
dc.descriptionProceeding of: 2012 IEEE Intelligent Vehicles Symposium (IV), Alcalá de Henares, Spain, June 3-7, 2012en
dc.description.abstractIn this paper a new contrast invariant descriptor for human detection in long-wave infrared images is proposed. It exploits local information histogram of orientations of phase coherence. Contrast in infrared images depends on the temperature of the object and the background, which makes gradient based descriptors less robust, especially in daylight conditions. The objective is to obtain a scale, brightness and contrast invariant descriptor that can successfully detect pedestrians in images taken with a cheap, temperature-sensitive, uncooled microbolometer. The descriptor, packed into grids is feed to a Support Vector Machine classifier. The algorithm has been tested in night and day sequences and its performance is compared with a day only descriptor: the histogram of oriented features (HOG).en
dc.description.sponsorshipThis work was supported by the Spanish Government through the Cicyt projects FEDORA (GRANT TRA2010- 20225-C03-01) and VIDAS-Driver (GRANT TRA2010- 21371-C03-02), and the Comunidad de Madrid through the project SEGVAUTO (S2009/DPI-1509).en
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitation2012 IEEE Intelligent Vehicles Symposium (IV), Pp. 117-122en
dc.identifier.doi10.1109/IVS.2012.6232242
dc.identifier.isbn978-1-4673-2119-8 (print)
dc.identifier.isbn978-1-4673-2118-1 (online)
dc.identifier.issn1931-0587
dc.identifier.publicationfirstpage117
dc.identifier.publicationlastpage122
dc.identifier.publicationtitle2012 IEEE Intelligent Vehicles Symposium (IV)en
dc.identifier.urihttps://hdl.handle.net/10016/17553
dc.identifier.uxxiCC/0000014610
dc.language.isoeng
dc.publisherIEEE
dc.relation.eventdate2012-06-03
dc.relation.eventplaceAlcalá de Henares
dc.relation.eventtitle2012 IEEE Intelligent Vehicles Symposium (IV)en
dc.relation.projectIDComunidad de Madrid. S2009/DPI-1509/SEGVAUTO
dc.relation.publisherversionhttp://dx.doi.org/10.1109/IVS.2012.6232242
dc.rights© 2012 IEEE
dc.rights.accessRightsopen access
dc.subject.otherBolometersen
dc.subject.otherInfrared imagesen
dc.subject.otherObject detectionen
dc.subject.otherPattern classificationen
dc.subject.otherPedestrian detectionen
dc.subject.otherSupport vector machinesen
dc.titleContrast invariant features for human detection in far infrared imagesen
dc.typeconference output*
dc.type.hasVersionAM*
dspace.entity.typePublication
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