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dc.contributor.authorTao, Qian
dc.contributor.authorRootseler, Robin van
dc.contributor.authorVeldhuis, Raymond
dc.contributor.authorGehlen, Stefan
dc.contributor.authorWeber, Frank
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorHühnlein, Detlef
dc.date.accessioned2019-05-15T09:23:30Z
dc.date.available2019-05-15T09:23:30Z
dc.date.issued2007
dc.identifier.isbn978-3-88579-202-4
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/22659
dc.description.abstractFusion is a popular practice to combine multiple classifiers or multiple modalities in biometrics. In this paper, optimal decision fusion (ODF) by AND rule and OR rule is presented. We show that the decision fusion can be done in an optimal way such that it always gives an improvement in terms of error rates over the classifiers that are fused. Both the optimal decision fusion theory and the experimental results on the FRGC 2D and 3D face data are given. Experiments show that the optimal decision fusion effectively combines the 2D texture and 3D shape information, and boosts the performance of the system.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e. V.
dc.relation.ispartofBIOSIG 2007: biometrics and electronic signatures
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-108
dc.titleOptimal Decision Fusion and Its Application on 3D Face Recognitionen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages15-23
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationDarmstadt
mci.conference.date12.-13. July 2007


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