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Proceedings Paper

3D face recognition based on the hierarchical score-level fusion classifiers
Author(s): Štěpán Mráček; Jan Váňa; Karolína Lankašová; Martin Drahanský; Michal Doležel
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Paper Abstract

This paper describes the 3D face recognition algorithm that is based on the hierarchical score-level fusion clas-sifiers. In a simple (unimodal) biometric pipeline, the feature vector is extracted from the input data and subsequently compared with the template stored in the database. In our approachm, we utilize several feature extraction algorithms. We use 6 different image representations of the input 3D face data. Moreover, we are using Gabor and Gauss-Laguerre filter banks applied on the input image data that yield to 12 resulting feature vectors. Each representation is compared with corresponding counterpart from the biometric database. We also add the recognition based on the iso-geodesic curves. The final score-level fusion is performed on 13 comparison scores using the Support Vector Machine (SVM) classifier.

Paper Details

Date Published: 29 May 2014
PDF: 12 pages
Proc. SPIE 9075, Biometric and Surveillance Technology for Human and Activity Identification XI, 907507 (29 May 2014); doi: 10.1117/12.2050547
Show Author Affiliations
Štěpán Mráček, Brno Univ. of Technology (Czech Republic)
Jan Váňa, Brno Univ. of Technology (Czech Republic)
Karolína Lankašová, Brno Univ. of Technology (Czech Republic)
Martin Drahanský, Brno Univ. of Technology (Czech Republic)
Michal Doležel, Brno Univ. of Technology (Czech Republic)


Published in SPIE Proceedings Vol. 9075:
Biometric and Surveillance Technology for Human and Activity Identification XI
Ioannis A. Kakadiaris; Walter J. Scheirer; Christoph Busch, Editor(s)

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