Recognition of facial expressions - Knowledge Based Systems ...

almost closed it obviously does not work. It creates a candidate list for the position of the
eyes and further detects the most appropriate two pixels to the known eye area
requirements. This can be avoided by setting a condition that finally detected pixels must
have the intensity above a given value. The other way would be to create a structure for
the alternative previous neural network to encode also the intensity of the candidate pixel
on the input neural layer.
Another limitation is that some calibration has to be done before the actual working
session. It consists in adjusting all the parameters related to the searched areas and
pixel/area characteristics.
Figure 26. Model 's characteristic points
So far only the positions of the pupils are detected. For the detection of the characteristic
points of each eye (Figure 26/ P1, P3, P5, P7, P2, P4, P6, P8), some processing has to be
done. A new parameter is computed as the distance between the pupils. That is used for
scaling all the distances so as to make the detection person independent.
The analysis starts again from the Sobel edge detector point. It further includes a
threshold pixel removing. Given the position of the pupils for both eyes, the procedure is
constrained to search for the pixels only in a given area around the pupil. Within the
searched area, all pixels are analyzed through the procedure of computing the mean and
variance as previously described. Based on the two values, some pixels are removed from
the image.
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