Selecting 3D Curves on the Nasal Surface using AdaBoost for Person Authentication

dc.contributor.authorBallihi, Lahoucineen_US
dc.contributor.authorAmor, B. Benen_US
dc.contributor.authorDaoudi, M.en_US
dc.contributor.authorSrivastava, A.en_US
dc.contributor.authorAboutajdine, D.en_US
dc.contributor.editorH. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkampen_US
dc.date.accessioned2013-04-25T14:10:28Z
dc.date.available2013-04-25T14:10:28Z
dc.date.issued2011en_US
dc.description.abstractThe main contribution of this paper is the use of an AdaBoost-based learning algorithm which builds a strong classifier from a set of weak classifiers associated with level curves in the nasal region of 3D faces. Its main application is person authentication. The basic idea is to represent nasal surfaces using indexed collections of level curves, and to compare shapes of noses by comparing the shape of their corresponding curves. AdaBoost considers each curve as a weak classifier and iteratively selects relevant curves to increase the authentication accuracy. We demonstrate these ideas on a subset taken from FRGC v2 (Face Recognition Grand Challenge) database. The proposed approach increases authentication performances relative to a simple fusion of scores from all curves.en_US
dc.description.sectionheadersShort Papersen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-31-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR11/101-104en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.2.10 [Computing Methodologies]: ARTIFICIAL INTELLIGENCE/ Vision and Scene Understanding-Shapeen_US
dc.titleSelecting 3D Curves on the Nasal Surface using AdaBoost for Person Authenticationen_US
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