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dc.contributor.authorTomé González, Pedro
dc.contributor.authorFiérrez Aguilar, Julián 
dc.contributor.authorFairhurst, Michael C.
dc.contributor.authorOrtega García, Javier 
dc.contributor.otherUAM. Departamento de Tecnología Electrónica y de las Comunicacioneses_ES
dc.date.accessioned2015-03-03T16:33:49Z
dc.date.available2015-03-03T16:33:49Z
dc.date.issued2010
dc.identifier.citationAdvances in Visual Computing: 6th International Symposium, ISVC 2010, Las Vegas, NV, (USA) November 29-December 1, 2010. Proceedings. Lecture Notes in Computer Science, Volumen 6453. Springer, 2010. 461-468en_US
dc.identifier.isbn978-3-642-17288-5 (print)en_US
dc.identifier.isbn978-3-642-17289-2 (online)en_US
dc.identifier.issn0302-9743 (print)en_US
dc.identifier.issn1611-3349 (online)en_US
dc.identifier.urihttp://hdl.handle.net/10486/664227
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-17289-2_44en_US
dc.descriptionProceedings of 6th International Symposium, ISVC 2010, Las Vegas, NV, (USA)en_US
dc.description.abstractAn experimental analysis of three acquisition scenarios for face recognition at a distance is reported, namely: close, medium, and far distance between camera and query face, the three of them considering templates enrolled in controlled conditions. These three representative scenarios are studied using data from the NIST Multiple Biometric Grand Challenge, as the first step in order to understand the main variability factors that affect face recognition at a distance based on realistic yet workable and widely available data. The scenario analysis is conducted quantitatively in two ways. First, we analyze the information content in segmented faces in the different scenarios. Second, we analyze the performance across scenarios of three matchers, one commercial, and two other standard approaches using popular features (PCA and DCT) and matchers (SVM and GMM). The results show to what extent the acquisition setup impacts on the verification performance of face recognition at a distance.en_US
dc.description.sponsorshipThis work has been partially supported by projects Bio-Challenge (TEC2009-11186), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and "Cátedra UAM-Telefónica".en_US
dc.format.extent9 pág.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringer Berlin Heidelberg
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rights© Springer-Verlag Berlin Heidelberg 2010
dc.subject.otherBiometricsen_US
dc.subject.otherFace recognition at a distanceen_US
dc.subject.otherFace recognition on the moveen_US
dc.titleAcquisition scenario analysis for face recognition at a distanceen_US
dc.typeconferenceObjecten
dc.typebookParten
dc.subject.ecienciaTelecomunicacioneses_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-642-17289-2_44
dc.identifier.doi10.1007/978-3-642-17289-2_44
dc.identifier.publicationfirstpage461
dc.identifier.publicationlastpage468
dc.identifier.publicationvolume6453
dc.relation.eventdateNovember 29 - December 1, 2010en_US
dc.relation.eventnumber6
dc.relation.eventplaceLas Vegas, NV (USA)en_US
dc.relation.eventtitle6th International Symposium on Visual Computing, ISVC 2010en_US
dc.relation.projectIDComunidad de Madrid. S2009/TIC-1485/CONTEXTSes_ES
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.contributor.groupAnálisis y Tratamiento de Voz y Señales Biométricas (ING EPS-002)es_ES
dc.rights.accessRightsopenAccessen
dc.authorUAMFierrez Aguilar, Julián (261834)
dc.authorUAMTome González, Pedro (263802)
dc.facultadUAMEscuela Politécnica Superior


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