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Real time face recognizer
Juráček, Aleš ; Přinosil, Jiří (referee) ; Richter, Miloslav (advisor)
My diploma thesis deals about face detection in picture. I try to outline problems of computer vision, artificial intelligence and machine learning. I described in details the proposed detection by Viola and Jones, which uses AdaBoost learning algorithm. This method was deliberately chosen for speed and detection accuracy. This detector was made in programming language C / C + + using the OpenCV library. To a final learning was used database of faces images „MIT CVCL Face Database“. The main goal was to propose the face detector utilizable also in video-sequences.
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Human-Machine Interface Based on Gestures
Charvát, Jaroslav ; Beran, Vítězslav (referee) ; Bartoň, Radek (advisor)
Master's thesis "Human-Machine Interface Based on Gestures" depicts the theoretical background of the computer vision and gesture recognition. It describes more in detail different methods that were used to create the application. Practical part of this thesis consists of the description of the developed program and its functionality. Using this application, user should be able to control computer by gestures of both right and left hands and also his head. The program is primarily based on the skin detection that is followed by the recognition of palms and head gestures. There were used two essential methods for these actions, AdaBoost and PCA.
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Application of Neural Networks for Human Face Localization
Libosvár, Jakub ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This bachelor thesis deals with detection and localization of human upright faces in images. At first, there are considered current methods. Then the face detection concept is presented. The thesis is focused on practical implementation of artificial neural network-based face detector designed by H. Rowley. Finally, training process and results of detector are discussed in more detail.
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Automatic face and facial feature detection
Krolikowski, Martin ; Kohoutek, Michal (referee) ; Přinosil, Jiří (advisor)
The master thesis presents an overview of face detection task in color, static images. Face detection term is posed in the context of various branches. Main concepts of face detection and also their relationships are described. Individual approaches are divided into groups and then define in turn. In the thesis is in detail described algorithm AdaBoost, which is selected on the basis of its properties. Especially speed of computation and good detection results are key features. In the scope of this work Viola-Jones detector was implemented. This detector was trained with face pictures from public accessible database. Combination of Viola-Jones detector with simple color detector is described. In the thesis is also presented experiment approach to facial features detection.
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Overview of methods for person identification using image processing
Palacka, Martin ; Březina, Lukáš (referee) ; Krejsa, Jiří (advisor)
This thesis deals with an overview of methods for person identification using image processing. The beginning of thesis is dedicated to the theoretical study of the skin segmentation method, its algorithm and different color spaces, which are used for identification by this method. The next algorithm is a method called boosted cascade of simple features, while focusing on description of this method, an OpenCV library, computing algorithm, image interpretation by integral image and speed of computation which is reached. The next chapter describes the PCA method, the principles of working, a description of the mathematical model, a study of gender recognition, the results and troubleshooting. The last described methods are fusion of facial strips and pixel patern based texture feature. At the end of this thesis there is the tested application of person identification and gender recognition and the results of the success of methods.
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Extraction of Face Covered by a Mask
Križka, Dominik ; Tinka, Jan (referee) ; Drahanský, Martin (advisor)
The bachelor thesis focuses on numerous techniques of extraction of a face covered by a mask, with assistance of the terahertz and infrared radiation. In order to resolve the issue, a database with photos of twelve people was created with various levels of face cover. The face extraction is then attempted with three techniques. First method uses ORB and SIFT descriptors on the face recognition. Descriptors were unable to successfully extract the masked face. The second technique is utilizes a facial landmark predictor. During the recognition of an unmasked face, the predictor is able to correctly represent regions of the face. With increased levels of coverage on face, it gets progressively more difficult to find facial landmarks correctly and inaccuracies occur. The last approach encodes the faces to numeric format and compares them between each other. The success rate of the extraction depends primarily on the quality of the model, which was trained on the neural network principle. The main contribution of the bachelor thesis, lies in the carried out experiments. In some cases of experiments, the identity of faces covered by scarf or balaclava were successfully revealed with usage of the infrared radiation and face encoding technique.
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The simulation of biometric protection systems working on the face recognition principle
Dubský, Milan ; Rampl, Ivan (referee) ; Atassi, Hicham (advisor)
The aim of this work is to realize a system in the Matlab-Simulink environment, which will be able to detect and recognize the human face from the input image. The created model will actually simulate the biometric security systems working on the principle of face recognition. The work is divided into two parts. In the first part, several methods for face detection from image are described. We focused on the symptomatic oriented and color segmentation methods. The pattern matching method is also described and implemented; the advantage ofthe pattern matching that it can be used either for face detection or face recognition. The second part of this work contains a description of the face recognition. Where PCA (Principal Component Analysis) are used for this task, this part of the work also includes experimental results of tests performed on our methods.
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Raspberry Pi: programming by means of Matlab/Simulink
Dadej, Vincent ; Švarc, Ivan (referee) ; Matoušek, Radomil (advisor)
The diploma thesis focuses on programming in the Matlab for the Raspberry Pi 3 platform. For the purpose of the presentation, there are two applications designed for Raspberry Pi that are using available hardware, camera and servos. The first application serves as colour object detecting and accurate tracking by using camera calibration. The second application serves as a face detection and recognition. These applications are implemented by modern methods and knowledge of computer vision. Tracking of the objects and face recognition are verified by an experiment that reveals the accuracy of the used methods.
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