Ocular Recognition Using Deep Features for Identity Authentication

dc.contributor.authorVizoni, Marcelo V. [UNESP]
dc.contributor.authorMarana, Aparecido N. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-12T01:34:15Z
dc.date.available2020-12-12T01:34:15Z
dc.date.issued2020-07-01
dc.description.abstractRecently, ocular biometrics has been gaining importance in Biometrics due to the poor performance obtained in some cases by biometric systems based on characteristics of the whole face. This paper presents a new method for person authentication based on ocular deep features, which are extracted from the ocular region of the face by using a very deep CNN (Convolutional Neural Network). Another interesting aspect of our method is that, instead of using directly the deep features as input for the authentication system, it uses the difference between the probe and gallery deep features. So, our method adopts a pairwise strategy. A binary support vector machine is trained to determine whether a given difference vector is genuine or impostor. The proposed new method based on such pairwise strategy was evaluated using the ocular left set of the UBIPr dataset and five pre-trained CNN architectures. When using the pre-trained VGG-Face the proposed method obtained a state-of-the-art result (3.18% of Equal Error Rate).en
dc.description.affiliationSão Paulo State University (UNESP)
dc.description.affiliationUnespSão Paulo State University (UNESP)
dc.format.extent155-160
dc.identifierhttp://dx.doi.org/10.1109/IWSSIP48289.2020.9145418
dc.identifier.citationInternational Conference on Systems, Signals, and Image Processing, v. 2020-July, p. 155-160.
dc.identifier.doi10.1109/IWSSIP48289.2020.9145418
dc.identifier.issn2157-8702
dc.identifier.issn2157-8672
dc.identifier.scopus2-s2.0-85089143654
dc.identifier.urihttp://hdl.handle.net/11449/199229
dc.language.isoeng
dc.relation.ispartofInternational Conference on Systems, Signals, and Image Processing
dc.sourceScopus
dc.subjectconvolutional neural networks
dc.subjectdeep learning
dc.subjectocular biometrics
dc.subjectperson authentication
dc.titleOcular Recognition Using Deep Features for Identity Authenticationen
dc.typeTrabalho apresentado em evento

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