Recognition of facial expressions - Knowledge Based Systems ...

of prototypic emotions (i.e., joy, surprise, anger, fear, disgust, and sadness). For the
available portion of the database, these six tasks and mouth opening in the absence of
other action units were coded by a certified FACS coder. Seventeen percent of the data
were comparison coded by a second certified FACS coder. Inter-observer agreement was
quantified with coefficient kappa, which is the proportion of agreement above what
would be expected to occur by chance (Cohen, 1960; Fleiss, 1981). The mean kappa for
inter-observer agreement was 0.86.
Image sequences from neutral to target display were digitized into 640 by 480 or 490
pixel arrays with 8-bit precision for grayscale values. The image format is “png”. Images
were labeled using their corresponding VITC.
FACS codes for the final frame in each image sequence were available for the analysis.
In some cases the codes have been revised. The final frame of each image sequence was
coded using FACS action units (AU), which are reliable descriptions of the subject's
expression.
In order to make the task of computing the model parameter values possible, a software
application was developed. It offered the possibility to manually plot certain points on
each image of the database in an easy manner. The other components of the system
automatically computed the values of the parameters so as to be ready for the training
step for the neuronal networks or for computing the probabilities table in the case of
BBN.
SMILE BBN library
SMILE [Structural Modeling, Inference, and Learning Engine] is a fully platform
independent library of C++ classes implementing graphical probabilistic and decision
theoretic models, such as Bayesian networks, influence diagrams, and structural equation
models. It was designed in a platform independent fashion as an object oriented robust
platform. It has releases starting from 1997. The interface is so defined as to provide the
developers with different tools for creating, editing, saving and loading of graphical
models. The most important feature is related to the ability to use the already defined
models for probabilistic reasoning and decision making under uncertainty. The release of
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