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Neutralisation des expressions faciales pour améliorer la reconnaissance du visage

Baptiste Chu 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 thesis, we aim to endow state of the art face recognition SDKs with robustness to simultaneous 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 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 show significant performance improvement and demonstrates the effectiveness of the proposed approach. Then, we aim to endow the state of the art FR SDKs with the capabilities to recognize faces in videos. Finally, we present different methods for improving biometric performances for specific cases.
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Baptiste Chu. Neutralisation des expressions faciales pour améliorer la reconnaissance du visage. Autre. Ecole Centrale de Lyon, 2015. Français. ⟨NNT : 2015ECDL0005⟩. ⟨tel-01225809⟩

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