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dc.contributor.authorVillamizar Vergel, Michael Alejandro
dc.contributor.authorSanfeliu Cortés, Alberto
dc.contributor.authorAndrade-Cetto, Juan
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2009-03-13T09:21:10Z
dc.date.available2009-03-13T09:21:10Z
dc.date.created2007
dc.date.issued2007
dc.identifier.citationVillamizar, Michael; Sanfeliu, Alberto; Andrade-Cetto, Juan. "Unidimensional multiscale local features for object detection under rotation and mild occlusions". 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), Girona, Catalunya, 2007. A: Lecture Notes in Computer Science, vol. 4477. Berlin, Alemanya: Springer Verlag, 2007, p. 645 - 651.
dc.identifier.urihttp://hdl.handle.net/2117/2683
dc.description.abstractIn this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogram has been used to compute local histograms in constant time.
dc.format.extentp. 645 - 651
dc.language.isoeng
dc.publisherSpringer Verlag
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject.lcshComputer vision
dc.titleUnidimensional multiscale local features for object detection under rotation and mild occlusions
dc.typePart of book or chapter of book
dc.subject.lemacVisió per ordinador
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
dc.description.peerreviewedPeer Reviewed
dc.subject.inspecClassificació INSPEC::Pattern recognition::Computer vision
dc.rights.accessOpen Access


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