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Face detection in image
Koudela, Ondřej ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
This work is basic overview over methods of face detection in picture and it's components. The main part of the work is an example of algorithm developed in MATLAB programming language for face detection based on skin color segmentation in different color spaces and their implementation in real time. The basic algorithm is discussed in several steps with shown results for each of color spaces and in the end of the work is evaluation of used methods. This work also includes a simulation of processing real-time detection in MATLAB Simulink.
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Facial expression recognition
Vránová, Markéta ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This project deals with automatic recognition of facial expression in colour pictures. At first, the colour-based face detection is accomplished, three colour spaces are used: RGB, HSV and YCbcCr. As next, the pictures are automatically cropped so that only the face region is present. It is accomplished by computing the borders of the face region based on knowledge of position of eyes, nose and mouth. From the face region, the feature vector is obtained using a bank of Gabor filters. The project introduces two different kinds of Gabor filters and proposes a new bank of filters. The feature vector is used as an input to the neural network. The neural network was trained on a set of pictures from AR database created for facial expression recognition. The output of the network is the facial expression the input picture was assigned to. This project mentions the testing for different settings of the neural network and presents and discuss the recognition results of the network.
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Face detection in image
Koudela, Ondřej ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
This work is basic overview over methods of face detection in picture and it's components. The main part of the work is an example of algorithm developed in MATLAB programming language for face detection based on skin color segmentation in different color spaces and their implementation in real time. The basic algorithm is discussed in several steps with shown results for each of color spaces and in the end of the work is evaluation of used methods. This work also includes a simulation of processing real-time detection in MATLAB Simulink.
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Facial expression recognition
Vránová, Markéta ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This project deals with automatic recognition of facial expression in colour pictures. At first, the colour-based face detection is accomplished, three colour spaces are used: RGB, HSV and YCbcCr. As next, the pictures are automatically cropped so that only the face region is present. It is accomplished by computing the borders of the face region based on knowledge of position of eyes, nose and mouth. From the face region, the feature vector is obtained using a bank of Gabor filters. The project introduces two different kinds of Gabor filters and proposes a new bank of filters. The feature vector is used as an input to the neural network. The neural network was trained on a set of pictures from AR database created for facial expression recognition. The output of the network is the facial expression the input picture was assigned to. This project mentions the testing for different settings of the neural network and presents and discuss the recognition results of the network.
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