Arama Sonuçları

Listeleniyor 1 - 3 / 3
  • Yayın
    Extraction and selection of muscle based features for facial expression recognition
    (IEEE Computer Soc, 2014-12-04) Benli, Kristin Surpuhi; Eskil, Mustafa Taner
    In this study we propose a new set of muscle activity based features for facial expression recognition. We extract muscular activities by observing the displacements of facial feature points in an expression video. The facial feature points are initialized on muscular regions of influence in the first frame of the video. These points are tracked through optical flow in sequential frames. Displacements of feature points on the image plane are used to estimate the 3D orientation of a head model and relative displacements of its vertices. We model the human skin as a linear system of equations. The estimated deformation of the wireframe model produces an over-determined system of equations that can be solved under the constraint of the facial anatomy to obtain muscle activation levels. We apply sequential forward feature selection to choose the most descriptive set of muscles for recognition of basic facial expressions.
  • Yayın
    İfade tanıma için yüz anatomisine dayalı öznitelikler
    (IEEE, 2014-04-23) Benli, Kristin Surpuhi; Eskil, Mustafa Taner
    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.
  • Yayın
    An observation based muscle model for simulation of facial expressions
    (Elsevier Science BV, 2018-05) Erkoç, Tuğba; Ağdoğan, Didem; Eskil, Mustafa Taner
    This study presents a novel facial muscle model for coding of facial expressions. We derive this model from unintrusive observation of human subjects in the progress of the surprise expression. We use a generic and single-layered face model which embeds major muscles of the human face. This model is customized onto the human subject's face on the first frame of the video. The last frame of the video is used to project a set of manually marked feature points to estimate the 3 dimensional displacements of vertices due to facial expression. Vertex displacements are used in a mass spring model to estimate the external forces, i.e. the muscle forces on the skin. We observed that the distribution of muscle forces resemble sigmoid or hyperbolic tangent functions. We chose hyperbolic tangent function as our base model and parameterized it using least squares. We compared the proposed muscle model with frequently used models in the literature.