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Semiautomatic Collection of Large Database of Human Faces
Michalík, Marek ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
The project is focused on methods of obtaining large number of images of human faces. Such database should then serve as a set of data for face detection and recognition by the means of supervised machine learning. The work deals with the basic principles of supervised machine learning and available data sets for this procedure. Project contains proposals of techniques and implementation of algorithms suitable for acquiring images from video and a concept of user interface for semi-automatic acceptation and annotation of located images.
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Human Face Recognition
Burián, Pavel ; Ševcovic, Jiří (referee) ; Herout, Adam (advisor)
The bachelor thesis deals with the problematic of the human face recognition in an image. It describes the face detection principles, methods used in recognition problematic and existing face data sets. Thesis is aimed on analysis, comparison and testing of the eigenface, fisherface and KDDA (Kernel Direct Discriminant Analysis) algorithms.
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Embedded video processing for surveillance systems
Gerych, Lukáš ; Polák, Ladislav (referee) ; Frýza, Tomáš (advisor)
The thesis includes the design and implementation of embedded system to capture static scenes and image evaluation for the surveillance system. It is performed on a tiny computer Raspberry Pi with ARM processor. Methods are provided for various types of detection in the image and their implementation using OpenCV libraries. It also deals with ways to access the system for the control and viewing records of detections.
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Face recognition
Maňkoš, Richard ; Mézl, Martin (referee) ; Kolář, Radim (advisor)
This diploma thesis deals with face recognition in digital pictures. The first part describes biometry and, shortly, characterizes biometrical methods which are the most oftenly used. In the second part is described the approach of face recognition in a picture. Specifically, it is described the method for face detection - Viola-Jones and method for face recognition - PCA, which will be implemented in Matlab. The last part, which is practical, describes the scheme for video-sequence recording, implementation of the PCA method in Matlab and discussion of the achieved results.
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Simple Gesture Recognition
Verner, Jan ; Beran, Vítězslav (referee) ; Potúček, Igor (advisor)
This bachelor thesis describes usability of DTW algorithm and it's variants for simple hand gesture detection. It recapitulates actual situation and findings in branch of computer vision and aims on methods for hand gesture recognition and common description of DTW algorithm.
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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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