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Smooth adaptive fitting of 3D face model for the estimation of rigid and nonrigid facial motion in video sequences / Yunshu Hou in Signal processing. Image communication, Vol. 26 N° 8-9 (Octobre 2011) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 26 N° 8-9 (Octobre 2011) . - pp. 550–566 Titre : Smooth adaptive fitting of 3D face model for the estimation of rigid and nonrigid facial motion in video sequences Type de document : texte imprimé Auteurs : Yunshu Hou, Auteur ; Ping Fan, Auteur ; Ilse Ravyse, Auteur Année de publication : 2012 Article en page(s) : pp. 550–566 Note générale : Electronique Langues : Anglais (eng) Mots-clés : Facial  analysis  Model-based  tracking  Motion-smoothness  constraints Résumé : We propose a 3D wireframe face model alignment for the task of simultaneously tracking of rigid head motion and nonrigid facial expressions in video sequences. The system integrates two levels: (i) at the low level, automatic and accurate location of facial features are obtained via a cascaded optimization algorithm of a 2D shape model, (ii) at the high level, we recover, via minimizing an energy function, the optimal motion parameters of the 3D model, namely the 3D rigid motion parameters and seven nonrigid animation (Action Unit) parameters. In this latter inference, a 3D face shape model (Candide) is automatically fitted to the image sequence via a least squares minimization of the energy, defined as the residual between the projected 3D wireframe model and the 2D shape model, meanwhile imposing temporal and spatial motion-smoothness constraints over the 3D model points. Our proposed system tackles many disadvantages of the optimization and training associated with active appearance models. Extensive fitting and tracking experiments demonstrate the feasibility, accuracy and effectiveness of the developed methods. Qualitative and quantitative performance of the proposed system on several facial sequences, indicate its potential usefulness for multimedia applications, as well as facial expression analysis. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596511000579 [article] Smooth adaptive fitting of 3D face model for the estimation of rigid and nonrigid facial motion in video sequences [texte imprimé] / Yunshu Hou, Auteur ; Ping Fan, Auteur ; Ilse Ravyse, Auteur . - 2012 . - pp. 550–566. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 26 N° 8-9 (Octobre 2011) . - pp. 550–566 Mots-clés : Facial  analysis  Model-based  tracking  Motion-smoothness  constraints Résumé : We propose a 3D wireframe face model alignment for the task of simultaneously tracking of rigid head motion and nonrigid facial expressions in video sequences. The system integrates two levels: (i) at the low level, automatic and accurate location of facial features are obtained via a cascaded optimization algorithm of a 2D shape model, (ii) at the high level, we recover, via minimizing an energy function, the optimal motion parameters of the 3D model, namely the 3D rigid motion parameters and seven nonrigid animation (Action Unit) parameters. In this latter inference, a 3D face shape model (Candide) is automatically fitted to the image sequence via a least squares minimization of the energy, defined as the residual between the projected 3D wireframe model and the 2D shape model, meanwhile imposing temporal and spatial motion-smoothness constraints over the 3D model points. Our proposed system tackles many disadvantages of the optimization and training associated with active appearance models. Extensive fitting and tracking experiments demonstrate the feasibility, accuracy and effectiveness of the developed methods. Qualitative and quantitative performance of the proposed system on several facial sequences, indicate its potential usefulness for multimedia applications, as well as facial expression analysis. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596511000579