Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/36233
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dc.contributorDepartment of Computing-
dc.creatorDhamecha, TI-
dc.creatorSingh, R-
dc.creatorVatsa, M-
dc.creatorKumar, A-
dc.date.accessioned2016-04-15T08:36:52Z-
dc.date.available2016-04-15T08:36:52Z-
dc.identifier.urihttp://hdl.handle.net/10397/36233-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2014 Dhamecha et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication: Dhamecha TI, Singh R, Vatsa M, Kumar A (2014) Recognizing Disguised Faces: Human and Machine Evaluation. PLoS ONE 9(7): e99212 is available at https://doi.org/10.1371/journal.pone.0099212en_US
dc.titleRecognizing disguised faces : human and machine evaluationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume9en_US
dc.identifier.issue7en_US
dc.identifier.doi10.1371/journal.pone.0099212en_US
dcterms.abstractFace verification, though an easy task for humans, is a long-standing open research area. This is largely due to the challenging covariates, such as disguise and aging, which make it very hard to accurately verify the identity of a person. This paper investigates human and machine performance for recognizing/verifying disguised faces. Performance is also evaluated under familiarity and match/mismatch with the ethnicity of observers. The findings of this study are used to develop an automated algorithm to verify the faces presented under disguise variations. We use automatically localized feature descriptors which can identify disguised face patches and account for this information to achieve improved matching accuracy. The performance of the proposed algorithm is evaluated on the IIIT-Delhi Disguise database that contains images pertaining to 75 subjects with different kinds of disguise variations. The experiments suggest that the proposed algorithm can outperform a popular commercial system and evaluates them against humans in matching disguised face images.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLoS one, 2014, v. 9, no. 7, e99212-
dcterms.isPartOfPLoS one-
dcterms.issued2014-
dc.identifier.isiWOS:000341306600003-
dc.identifier.scopus2-s2.0-84904315182-
dc.identifier.pmid25029188-
dc.identifier.eissn1932-6203en_US
dc.identifier.rosgroupid2014003431-
dc.description.ros2014-2015 > Academic research: refereed > Publication in refereed journalen_US
dc.description.validate201811_a bcmaen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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