Show simple item record

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.accessioned2010-09-29T17:15:00Z
dc.date.available2010-09-29T17:15:00Z
dc.date.issued2009-06-12
dc.identifier.isbn978-3-642-02123-7
dc.identifier.urihttp://hdl.handle.net/2117/9181
dc.description.abstractThe present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. The first one learns discriminant local features corresponding to pedestrian parts and the second one selects and combines these boosted features into a robust class classifier. In contrast of other works, our features are based on local differences over Histograms of Oriented Gradients (HoGs). Experiments carried out to a public dataset of pedestrian images show good performance with high classification rates
dc.format.extent8 p.
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.titleLocal boosted features for pedestrian detection
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.identifier.doi10.1007/978-3-642-02172-5_18
dc.subject.inspecClassificació INSPEC::Pattern recognition::Computer vision
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-642-02172-5_18
dc.rights.accessOpen Access
drac.iddocument2175794
dc.description.versionPreprint


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder