İfade tanıma için yüz anatomisine dayalı öznitelikler
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Dosyalar
Tarih
2014-04-23
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Bu çalışmada yüz ifadesi tanıma için kas kuvvetlerine dayalı yeni öznitelikler öneriyoruz. Yüz üzerinde seçtiğimiz noktaların video üzerindeki hareketlerini izleyerek kas kuvvetlerini çözüyoruz. Yüz noktaları, ilk video çerçevesi üzerinde, kas kuvvet alanları üzerinde ilklendirilir. Bu noktalar optik akış algoritması ile izlenir. Noktaların devinimleri yüzün 3 boyutlu yönelimi ve yüz ifadesine dayalı bağıl devinimleri kestirmek için kullanılır. İnsan yüzünü yaylarla, artık-belirtilmiş doğrusal bir denklem sistemi olarak modelliyoruz. Bu sistemi yüz anatomisi kısıtı altında, kas kuvvetleri için çözüyoruz. Ardışık ileri seçim yaparak, temel yüz ifadeleri için en betimleyici kas kümesini belirliyoruz.
In this study we propose a set of anatomy based features for facial expression recognition. The muscle forces that constitute an expression are solved by tracking carefully selected facial feature points. These points are initialized in the muscular regions of influence on the first frame of the video. They are tracked using the optical flow algorithm. The displacements of facial feature points are used for estimation of 3 dimensional head orientation and deformations due to expressions. We model human face with springs as an over-determined and linear system of equations. This system is solved under the constraint of facial anatomy for muscular activities. We use sequential forward selection to determine the most descriptive set of features for classification of basic expressions.
In this study we propose a set of anatomy based features for facial expression recognition. The muscle forces that constitute an expression are solved by tracking carefully selected facial feature points. These points are initialized in the muscular regions of influence on the first frame of the video. They are tracked using the optical flow algorithm. The displacements of facial feature points are used for estimation of 3 dimensional head orientation and deformations due to expressions. We model human face with springs as an over-determined and linear system of equations. This system is solved under the constraint of facial anatomy for muscular activities. We use sequential forward selection to determine the most descriptive set of features for classification of basic expressions.
Açıklama
Anahtar Kelimeler
Anatomi, Kas kuvveti, Öznitelik, Yüz ifadesi, 3D Head deformation, 3D Head orientation, Anatomy, Anatomy based feature, Basic expression classification, Computational modeling, Computer vision, Conferences, Emotion recognition, Face, Face recognition, Facial expression recognition, Facial feature point, Facial expression recognition, Facial expressions, Feature, Gesture recognition, Human computer interaction, Image classification, Linear system of equations, Linear systems, Models, Muscle force, Muscles, Muscular activity, Optical flow algorithm, Recognition FER, Sequential forward selection, Signal processing
Kaynak
WoS Q Değeri
N/A
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Sayı
Künye
Benli, K. S. & Eskil, M. T. (2014). Anatomy based features for facial expression recognition. Paper presented at the 2014 22nd Signal Processing and Communications Applications Conference (SIU), 172-175. doi:10.1109/SIU.2014.6830193
