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This dissertation thesis deals with the automatic system for basic emotional facial expressions recognition from static images. Generally the system is divided into the three independent parts, which are linked together in some way. The first part deals with automatic face detection from color images. In this part they were proposed the face detector based on skin color and the methods for eyes and lips position localization from detected faces using color maps. A part of this is modified Viola-Jones face detector, which was even experimentally used for eyes detection. The both face detectors were tested on the Georgia Tech Face Database. Another part of the automatic system is features extraction process, which consists of two statistical methods and of one method based on image filtering using set of Gabor’s filters. For purposes of this thesis they were experimentally used some combinations of features extracted using these methods. The last part of the automatic system is mathematical classifier, which is represented by feed-forward neural network. The automatic system is utilized by adding an accurate particular facial features localization using active shape model. The whole automatic system was benchmarked on recognizing of basic emotional facial expressions using the Japanese Female Facial Expression database. |
