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Classification of Human Facial Expression:. Edition No. 1
VDM Publishing House, Aug 2008, Pages: 180
This book describes a computer vision system for
detection and classification of 7 basic facial
expressions. Facial expressions are communicated by
subtle changes in one or more discrete features such
as tightening the lips, raising the eyebrows, opening
and closing of eyes or certain combination of them,
which can be identified through monitoring the
changes in muscles movements located around the above
regions. In our research, an analytic face
representation consists of 15 feature points has been
used that identifies the principle muscle actions and
provides visual observation of the discrete features
responsible for each of the 7 basic emotions. Feature
points from the region of mouth have been detected by
segmenting the lip contour applying a variational
formulation of the level set method. A multi-detector
approach of facial feature point detection has been
utilized for identifying the points of interest from
the region of eye, eyebrow and nose. Feature vectors
composed of 15 features are then obtained from these
feature points and used to train a SVM classifier so
that the system can classify facial expressions from
an unknown face image with a certain level of accuracy.
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