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Reconnaissance d'Expressions Faciale 3D Basée sur l'Analyse de Forme et l'Apprentissage Automatique

Ahmed Maalej 1 
LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : Facial expression recognition is a challenging task, which has received growing interest within the research community, impacting important applications in fields related to human computer interaction (HCI). Toward building human-like emotionally intelligent HCI devices, scientists are trying to include human emotional state in such systems. The recent development of 3D acquisition sensors has made 3D data more available, and this kind of data comes to alleviate the problems inherent in 2D data such as illumination, pose and scale variations as well as low resolution. Several 3D facial databases are publicly available for the researchers in the field of face and facial expression recognition to validate and evaluate their approaches. This thesis deals with 3D facial expression recognition (FER) problem and proposes an approach based on shape analysis to handle both 3D static and 3D dynamic FER tasks. Our approach includes the following steps: first, a curve-based representation of the 3D face model is proposed to describe facial features. Then, once these curves are extracted, their shape information is quantified using a Riemannian framework. We end up with similarity scores between different facial local shapes constituting feature vectors associated with each facial surface. Afterwards, these features are used as entry parameters to some machine learning and classification algorithms to recognize expressions. Exhaustive experiments are derived to validate our approach and recognition results of 98.81% for 3D FER and 93.83% for 4D FER are attained and are compared to the related work achievements.
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Submitted on : Wednesday, August 29, 2012 - 3:34:53 PM
Last modification on : Friday, October 23, 2020 - 4:37:13 PM
Long-term archiving on: : Friday, December 16, 2016 - 8:38:08 AM


  • HAL Id : tel-00726298, version 1



Ahmed Maalej. Reconnaissance d'Expressions Faciale 3D Basée sur l'Analyse de Forme et l'Apprentissage Automatique. Intelligence artificielle [cs.AI]. Université des Sciences et Technologie de Lille - Lille I, 2012. Français. ⟨NNT : ⟩. ⟨tel-00726298⟩



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