Facial expression recognition based on anatomy
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Dosyalar
Tarih
2014-02
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Academic Press Inc Elsevier Science
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, we propose a novel approach to facial expression recognition that capitalizes on the anatomical structure of the human face. We model human face with a high-polygon wireframe model that embeds all major muscles. Influence regions of facial muscles are estimated through a semi-automatic customization process. These regions are projected to the image plane to determine feature points. Relative displacement of each feature point between two image frames is treated as an evidence of muscular activity. Feature point displacements are projected back to the 3D space to estimate the new coordinates of the wireframe vertices. Muscular activities that would produce the estimated deformation are solved through a least squares algorithm. We demonstrate the representative power of muscle force based features on three classifiers; NB, SVM and Adaboost Ability to extract muscle forces that compose a facial expression will enable detection of subtle expressions, replicating an expression on animated characters and exploration of psychologically unknown mechanisms of facial expressions.
Açıklama
Anahtar Kelimeler
Facial anatomy, Muscle force, Features, Facial action coding system, Active appearance models, Robust face tracking, Information fusion, Motion, Video, Images, Face recognition, Adaptive boosting, Gesture recognition, Muscle, Facial expression recognition, Least squares algorithm, Relative displacement
Kaynak
Computer Vision and Image Understanding
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
119
Sayı
Künye
Eskil, M. T. & Benli, K. S. (2014). Facial expression recognition based on anatomy. Computer Vision and Image Understanding, 119, 1-14. doi:10.1016/j.cviu.2013.11.002
