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Masked face detection
Malý, Ondřej ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
The aim of this work is to study and test current methods for face detection on veiled faces and evaluate the results. In the first chapter, five selected methods are theoretically analyzed and in the second chapter the individual methods are evaluated, both for the Wider Face file and for the actual set of photos with veiled faces. Subsequently, the Dlib CNN method is improved for better detection of veiled faces and reprogrammed to detect the degree of veil from the tested image
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Software for Digital Mixing Console
Zoň, Robin ; Přinosil, Jiří (referee) ; Schimmel, Jiří (advisor)
This thesis describes the design and implementation of a software for digital mixing console built on the Windows platform. This software is designed to offer real-time multi-channel audio processing using multiple input and output units, signal routing between these units and insertion and management of VST plug-in modules. The software uses an audio interface connected with ASIO technology. The thesis is divided into several applications. Main application which computes audio samples and allows insertion and management of plug-ins is programmed in C++ using JUCE technology. This application can be controlled with its own local graphical interface or with web control interface, which is programmed in TypeScript with the use of React technology. Web interface allows user to control VST plug-in modules with its own custom implementation of plug-in control.
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Deep learning based face recognition in real conditions
Horňáková, Veronika ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis explores the area of face recognition using deep learning technique. Face recognition is used for two main reasons: verification and identification. In this thesis we describe the techniques of deep learning, mostly the convolutional neural networks, which are the most significant method for processing images - detection, classification and segmentation of the image. The process of face recognition is divided into four main steps: face detection, face selection, face extraction and face classification. We chosen three of the existing programs for face recognition (OpenFace, FaceNet and Face_Recognition), which are described in this thesis, in particular the principle of the human face recognition. Thanks to the tests with the data set of Labeled Faces in the Wild (LFW) we could specify the accuracy and the time requirement of each application. Testing of FaceNet and Face_Recognition ran on real data with face detection in video with complicated conditions. The test compares two images and tries to determine if is the same person. The test results are show in graph and table.
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Recognition of persons clothing in the video signal
Mlýnková, Barbora ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This paper is dealing with the detection clothes characteristics in the picture, for the use of person identification. These characteristics are described and categorized. It also deals with the design of the database structure, which works with masks and categories of characteristics for their processing. This work uses haar cascades to detect face and to determine the position of clothing for the purpose of color detection
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Detection of selected audio events in a real environment
Kowolowski, Alexander ; Burget, Radim (referee) ; Přinosil, Jiří (advisor)
This work deals with methods for the detection of dangerous events, in this case gunshots, in a real environment. First of all, a testing and training database of sounds from the MIVIA database was created. In this database, the files were contained in six versions of signal-to-noise ratio, so the subsequent testing of the selected methods took place for the various shuffled files, and it was found that some methods are more accurate for cleaner recordings than others, but less accurate for more noisy ones. For the typical feature extraction from the input sound, the mel-frequency cepstral coefficients method was always used. In the thesis, the methods of support vector machines and ensemble of a number of weak classifiers are gradually tested on the created databases. These methods are then further optimized, for example by using statistical variables, and after optimization they achieve better results, as expected. In the work, two scripts were created, where one created a training database and on this data trained the classifier and the other created the test database, tested the selected classifier and obtained the results. The results are processed by confusion matrix and several proportional variables such as accuracy, sensitivity, specificity and others are calculated. These results are always listed in the relevant chapter of the thesis in the tables and column charts and are properly commented on.
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Real-time voice command recognition system
Šíbl, Evžen ; Kiac, Martin (referee) ; Přinosil, Jiří (advisor)
The bachelor thesis deals with the development of a system for voice command recognition. The classifier of this system was created using a neural network. In this thesis you will learn about the history and problems of speech recognition. A system has been created that detects a section in a recording containing a speech signal, which then uses the classifier to decide what word from the word table it is. Three models with the same architecture but with different training data were created. These models were then compared with each other. A simple user interface was created for the resulting system.
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Superresulution of photography using deep neural network
Holub, Jiří ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
This diploma thesis deals with image super-resolution with conservation of good quality. Firstly, there are described state of the art methods dealing with this problem, as well as principles of neural networks with focus on convolutional ones. Finally, there is described a few models of convolutional neural network for image super-resolution to double size, which have been trained, tested and compared on newly created database with pictures of people.
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Face detection in image
Malach, Tobiáš ; Přinosil, Jiří (referee) ; Mézl, Martin (advisor)
This paper presents an overview of face detection methods. Keywords and basic principles of classification of images and it’s parts are explained. Significant part of this paper is occupied with presentation of Viola-Jones detector and it’s implementation in Matlab. Detector Viola-Jones ranks among the most used methods for face detection in practice, which was the reason for detailed analysis and subsequent implementation. Detector is theoretically described, basic steps of algorithm and training algorithm are discussed. Based on theoretical analysis, detector is implemented in Matlab. Properties of implemented detector are objectively evaluated and compared with of two different implementations.
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