Robust Facial Features Tracking Using Geometric Constraints and Relaxation

Abstract : This work presents a robust technique for tracking a set of detected points on a human face. Facial features can be manually selected or automatically detected. We present a simple and efficient method for detecting facial features such as eyes and nose in a color face image. We then introduce a tracking method which, by employing geometric constraints based on knowledge about the configuration of facial features, avoid the loss of points caused by error accumulation and tracking drift. Experiments with different sequences and comparison with other tracking algorithms, show that the proposed method gives better results with a comparable processing time.
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Communication dans un congrès
IEEE MMSP 09, 11th IEEE International Workshop on MultiMedia Signal Processing, Oct 2009, Rio de Janeiro, Brazil. pp.1-6, 2009, <10.1109/MMSP.2009.5293329>
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00584681
Contributeur : Désiré Sidibé <>
Soumis le : samedi 9 avril 2011 - 16:31:08
Dernière modification le : lundi 12 septembre 2016 - 15:30:06
Document(s) archivé(s) le : dimanche 10 juillet 2011 - 02:30:07

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Désiré Sidibé, Philippe Montesinos, Alain Trémeau. Robust Facial Features Tracking Using Geometric Constraints and Relaxation. IEEE MMSP 09, 11th IEEE International Workshop on MultiMedia Signal Processing, Oct 2009, Rio de Janeiro, Brazil. pp.1-6, 2009, <10.1109/MMSP.2009.5293329>. <hal-00584681>

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