Show simple item record

dc.contributor.authorDrozdowski, Pawel
dc.contributor.authorStruck, Florian
dc.contributor.authorRathgeb, Christian
dc.contributor.authorBusch, Christoph
dc.date.accessioned2018-12-17T11:40:47Z
dc.date.available2018-12-17T11:40:47Z
dc.date.created2018-12-14T10:24:32Z
dc.date.issued2018
dc.identifier.isbn978-1-4799-7061-2
dc.identifier.urihttp://hdl.handle.net/11250/2577914
dc.description.abstractFeature vectors extracted from biometric characteristics are often represented using floating point values. It is, however, more appealing to store and compare feature vectors in a binary representation, since it generally requires less storage and facilitates efficient comparators which utilise intrinsic bit operations. Furthermore, the binary representations are very often necessary for some specific application scenarios, e.g. template protection and indexing. In recent years, usage of deep neural networks for facial recognition has vastly improved the biometric performance of said systems. In this paper, various binarisation schemes are applied to such feature vectors and benchmarked for biometric performance. It is shown that with only a negligible drop in biometric performance, the storage space and computational requirements can be vastly decreased.nb_NO
dc.language.isoengnb_NO
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)nb_NO
dc.relation.ispartof2018 25th IEEE International Conference on Image Processing (ICIP)
dc.titleBenchmarking Binarisation Schemes for Deep Face Templatesnb_NO
dc.typeChapternb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber191-195nb_NO
dc.identifier.doi10.1109/ICIP.2018.8451291
dc.identifier.cristin1643143
dc.description.localcode© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.nb_NO
cristin.unitcode194,63,30,0
cristin.unitnameInstitutt for informasjonssikkerhet og kommunikasjonsteknologi
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode1


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record