3D-aided face recognition robust to expression and pose variations

Baptiste Chu 1 Sami Romdhani Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Expression and pose variations are major challenges for reliable face recognition (FR) in 2D. In this paper, we aim to endow state of the art face recognition SDKs with robustness to facial expression variations and pose changes by using an extended 3D Morphable Model (3DMM) which isolates identity variations from those due to facial expressions. Specifically, given a probe with expression, a novel view of the face is generated where the pose is rectified and the expression neutralized. We present two methods of expression neutralization. The first one uses prior knowledge to infer the neutral expression image from an input image. The second method, specifically designed for verification, is based on the transfer of the gallery face expression to the probe. Experiments using rectified and neutralized view with a standard commercial FR SDK on two 2D face databases, namely Multi-PIE and AR, show significant performance improvement of the commercial SDK to deal with expression and pose variations and demonstrates the effectiveness of the proposed approach.
Type de document :
Communication dans un congrès
27/06/2014. 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2014, Columbus, Ohio, United States. pp.1-8, 2014
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https://hal.archives-ouvertes.fr/hal-01271809
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : mardi 9 février 2016 - 16:19:24
Dernière modification le : mercredi 10 février 2016 - 01:06:01

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  • HAL Id : hal-01271809, version 1

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Baptiste Chu, Sami Romdhani, Liming Chen. 3D-aided face recognition robust to expression and pose variations. 27/06/2014. 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2014, Columbus, Ohio, United States. pp.1-8, 2014. 〈hal-01271809〉

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