Benchmarking asymmetric 3D-2D face recognition systems

Xi Zhao Wuming Zhang 1 Evangelopoulos G. 2 Di Huang Shah S.K. Yunhong Wang Ioannis A. Kakadiaris Liming Chen 3
1 ICJ - Institut Camille Jordan [Villeurbanne]
2 School of E.C.E - School of of Electrical and Computer Engineering [Athens]
3 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : — Asymmetric 3D-2D face recognition (FR) aims to recognize individuals from 2D face images using textured 3D face models in the gallery (or vice versa). This new FR scenario has the potential to be readily deployable in field applications while still keeping the advantages of 3D FR solutions of being more robust to pose and lighting variations. In this paper, we propose a new experimental protocol based on the UHDB11 dataset for benchmarking 3D-2D FR algorithms. This new experimental protocol allows for the study of the performance of a 3D-2D FR solution under pose and/or lighting variations. Furthermore, we also benchmarked two state of the art 3D- 2D FR algorithms. One is based on the Annotated Deformable Model (using manually labeled landmarks in this paper) using manually labeled landmarks whereas the other makes use of Oriented Gradient Maps along with an automatic pose estimation through random forest.
Type de document :
Communication dans un congrès
IEEE. Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on Biometrics Compendium, IEEE, Apr 2013, Shanghai, China. pp.1-8, 2013, 〈10.1109/FG.2013.6553819〉
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https://hal.archives-ouvertes.fr/hal-01339319
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : mercredi 29 juin 2016 - 15:52:44
Dernière modification le : jeudi 19 avril 2018 - 14:38:06

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Xi Zhao, Wuming Zhang, Evangelopoulos G., Di Huang, Shah S.K., et al.. Benchmarking asymmetric 3D-2D face recognition systems. IEEE. Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on Biometrics Compendium, IEEE, Apr 2013, Shanghai, China. pp.1-8, 2013, 〈10.1109/FG.2013.6553819〉. 〈hal-01339319〉

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