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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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Establishing speaker's age and sex
Rendek, Tomáš ; Pfeifer, Václav (referee) ; Atassi, Hicham (advisor)
This work deals with speaker´s age and gender recognition. At the beginning it introduces the practical usage of this application and discusses the solutions available. The theoretical part of the thesis specifies the feature extraction and reduction methods and speech databases used in the experiments. The practical part describes the recognizer implemented in the Emotional tool and in two chapters describes the individual experiments. Regarding speaker´s gender estimation; we focused on the impact of the emotional state and speaker's age on the classification process. The two remain experiments were dedicated for general gender estimation performed by using two different classifiers – GMM and k-NN. These two classifiers were used in age estimation as well. In this case, four Group of age was formed and two different feature sets namely: segmental and suprasegmental were exploited four groups
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Face Detection
Štrba, Miroslav ; Juránek, Roman (referee) ; Hradiš, Michal (advisor)
This bachelor thesis contains overview of actual face detection methods using classifier. It also contains description of creating system for face detection. There are described different methods for classifier training in first part. There is analysis, which preceded creation of system focused on black-and-white picture, in second part. Implemented system is using WaldBoost algorithm and Haar features. There is option to use particle filter in video.
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Real-time Facial Feature Tracking
Peloušek, Jan ; Mekyska, Jiří (referee) ; Přinosil, Jiří (advisor)
This thesis considers the problematic of the object recognition in a digital picture, particularly about the human face recognition and its components. There are described the basics of the computer vision, the object detector Viola-Jones, its computer realization with help of the OpenCV libraries and the test results. This thesis also describes the accurate system of the facial features detection per the algorithm of the Active Shape Models and also related mechanism of the classifier training, including the software implementation.
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Defects classification
Benda, Jan ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
The thesis deals with a concept and creation of classifiers of defects found on continuous production lines. The first part presents an overview of methods used for image classification and a analysis of defects. The main part of the thesis consist of a description of created classifier interface and graphical user interface for classifier. The last part sums up reliability of each implemented classifer.
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Face Detection in Video
Kolman, Aleš ; Řezníček, Ivo (referee) ; Polok, Lukáš (advisor)
The project is focused on face detection in video. Firstly, it contains a summary of basic color models. Secondly, you can find the description and comparison of the basic methods for detection of human skin with a practical example of implementation of parametric detector. Thirdly, a theoretical basis for face detection and face tracking in a video containing a list of basic concepts and methods of this issue follows. Greater emphasis is placed on the description of machine learning algorithm AdaBoost and description of the possible application of the Kalman filter for the purpose of face tracking. Design, implementation and testing of library accomplished within the master thesis are listed in the final part of this thesis.
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Cards Recognition Using Android
Klusoň, Martin ; Polok, Lukáš (referee) ; Pavelková, Alena (advisor)
This work deals with design of an application for the mobile operating system Android. Application recognize playing cards and their values from image from camera device. Application helps to count points in game Rummy. Recognition is solved by a combination of three cascaded classifiers. Solutions based on keypoint detection and OCR proved useless. The application detects values of cards (excluding jokers), not their colors.
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Automatic Photography Categorization
Veľas, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to create an application, which is would be able to achieve sufficient precision and computation speed of categorization. Basic solution involves detection of interesting points, extraction of feature vectors, creation of visual codebook by clustering, using k-means algorithm and representing visual codebook by k-dimensional tree. Photography is represented by bag of words - histogram of presence of visual words in a particular photo. Support vector machines (SVM) was used in role of classifier. Afterwards the basic solution is enhanced by dividing picture into cells, which are processed separately, computing color correlograms for advanced image description, extraction of feature vectors in opponent color space and soft assignment of visual words to extracted feature vectors. The end of this thesis concerns to experiments of of above mentioned techniques and evaluation of the results of image categorization on their usage.
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Optical side channel
Kolofík, Josef ; Mačák, Jaromír (referee) ; Martinásek, Zdeněk (advisor)
This thesis deals with the optical side channel and using a neural network as classifier of data. The first part deals with the basics of cryptography and attacks on the cryptographic module. The second part deals with methods of decapsulation the microcontroller, decapsulation technological processes and methods of detection of photons. The third part deals with the use of neural networks as the basis of recognition and data classification software. In conclusion, the thesis describes the procedure for creating this software, analyzes the source code and tests the functionality of this solution.
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