Real-time recognition of six basic facial expressions

This paper deals with the real-time recognition of six basic-facial expressions. In order to obtain the center position of both pupils, we obtain the brightness by using a CCD camera, along a vertical line crossing over the pupil and eyebrow as base data and calculate the cross-correlation between base data and that in the given image. We extract the position of right and left pupils separately. As the facial information for utilizing the recognition of facial expression, we use brightness data of 13 vertical lines (facial information), determined empirically and including the areas of eyes, eyebrows and mouth. Then we acquire the facial information of a basic facial expressions for 30 subjects whose face images have already been obtained. Since we use a layer-type neural network for recognition of facial expressions, the facial information for some of 30 subjects is used for training the neural network. We found that, when we used 15 subjects for the network training, the correct recognition ratio reached 85%. and the total time for detecting right and left pupil positions plus the recognition of facial expression was about 60 ms per one recognition cycle