Facial action recognition for facial expression analysis from static face images.
Automatic recognition of facial gestures (i.e., facial muscle activity) is rapidly becoming an area of intense interest in the research field of machine vision. In this paper, we present an automated system that we developed to recognize facial gestures in static, frontal- and/or profile-view color face images. A multidetector approach to facial feature localization is utilized to spatially sample the profile contour and the contours of the facial components such as the eyes and the mouth. From the extracted contours of the facial features, we extract ten profile-contour fiducial points and 19 fiducial points of the contours of the facial components. Based on these, 32 individual facial muscle actions (AUs) occurring alone or in combination are recognized using rule-based reasoning. With each scored AU, the utilized algorithm associates a factor denoting the certainty with which the pertinent AU has been scored. A recognition rate of 86% is achieved.
Department of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628 CD Delft, The Netherlands. M.Pantic@ewi.tudelft.nl
Maja
M
Pantic
Leon J M
LJ
Rothkrantz
D000465:Algorithms; D001185:Artificial Intelligence; D005145:Face / Q000033:anatomy & histology* / Q000502:physiology*; D005149:Facial Expression; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated; D010781:Photography / Q000379:methods; D011187:Posture / Q000502:physiology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity