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3-D Face Recognition With Local Shape Descriptors

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dc.contributor.author Inan, Tolga
dc.contributor.author Halici, Ugur
dc.date.accessioned 2019-06-24T08:23:35Z
dc.date.available 2019-06-24T08:23:35Z
dc.date.issued 2012
dc.identifier.issn 1556-6013
dc.identifier.issn 1556-6021
dc.identifier.uri https://acikerisim.tedu.edu.tr/xmlui/handle/20.500.12485/51
dc.identifier.uri https://doi.org/10.1109/TIFS.2012.2186293
dc.description.abstract In this paper, we present a novel automatic approach based on local shape descriptors to discriminate 3-D facial scans of different individuals. Our approach begins with registration, smoothing and uniform resampling of 3-D face data. Then, uniformly resampled 3-D face data are used to generate shape index, curvedness, gaussian and mean curvature values on each point of the data. Hence we obtain 2-D matrices of shape index, curvedness, gaussian and mean curvature values representing 3-D geometry information. SIFT descriptors are applied to 2-D matrices and high dimensional feature vector having shape information is obtained. Finally, high dimensional feature vector is projected to the low dimensional subspace where projection matrix is calculated by linear discriminant analysis. Features in this low dimensional subspace are compared by using cosine distance similarity metric. Proposed method is shown to have 98.35% and 98.25% detection rates at 0.001 false alarm rate for All vs. All and ROC3 experiments respectively on FRGC v2.0 database. To the best of our knowledge, these are the best results among similar studies available in 3-D face recognition literature. en_US
dc.language.iso en en_US
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA en_US
dc.subject Engineering en_US
dc.subject Computer Science en_US
dc.subject Theory & Methods en_US
dc.subject Electrical & Electronic en_US
dc.title 3-D Face Recognition With Local Shape Descriptors en_US
dc.type Article en_US
dc.relation.journal IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
dc.relation.journal IEEE Transactions on Information Forensics and Security
dc.identifier.issue 2
dc.identifier.startpage 577
dc.identifier.endpage 587
dc.identifier.volume 7


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