Title :
Anatomy based features for facial expression recognition
Author :
Benli, Kristin S. ; Eskil, M. Taner
Author_Institution :
FMV IrIK Univ., Istanbul, Turkey
Abstract :
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.
Keywords :
emotion recognition; face recognition; image classification; 3D head deformation; 3D head orientation; anatomy based feature; basic expression classification; facial expression recognition; facial feature point; muscle force; muscular activity; optical flow algorithm; Computational modeling; Computer vision; Conferences; Face; Face recognition; Muscles; Signal processing; Facial expressions; anatomy; feature; muscle force;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
DOI :
10.1109/SIU.2014.6830193