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Face Recognition in Security and Surveillance Camera Systems
Malach, Tobiáš ; Říha, Kamil (referee) ; Hudec,, Róbert (referee) ; Poměnková, Jitka (advisor)
Tato práce se zabývá zvýšením úspěšnosti rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. K dosažení tohoto cíle je využit nový přístup - optimalizace vzorů obličejů. Optimalizace tvorby vzorů umožní vytvořit vzory, které zajistí zvýšení úspěšnosti rozpoznání. Měření a další zvyšování úspěšnosti rozpoznávání obličejů vyžaduje naplnění následujících dílčích cílů této práce. Prvním cílem je návrh a sestavení reprezentativní databáze obličejů, která umožní dosáhnout věrohodných a statisticky spolehlivých výsledků rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. Druhým cílem je vytvoření metodiky pro statisticky spolehlivé porovnání výsledků, která umožní konstatování relevantních závěrů. Třetím cílem je výzkum tvorby vzorů a jejich optimalizace. Z dosažených výsledků vyplývá, že optimalizace tvorby vzorů zvyšuje úspěšnost rozpoznávání v uvedených a náročných aplikacích typicky o 4-8%, a v některých případech i 15%. Optimalizace tvorby vzorů přispívá použitelnosti rozpoznávání obličejů v uvedených aplikacích.
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Estimation and analysis of speech signal periodicity
Malucha, Jan ; Poměnková, Jitka (referee) ; Sigmund, Milan (advisor)
Theoretical part starts with a short introduction to speech signals and short time analysis method. Concept of periodicity is clarified. This is followed by analysis of the speech signal parameters - voiced/unvoiced classification, intonation and short time period similarity. Next the overview of methods used to analyze the mentioned parameters together with concepts of their algorithms is provided. These methods include ZCR, STE, HNR, ACF, NCC, AMDF and DTW. Algorithms using the methods with supporting preprocessing algorithms were programmed in MATLAB for practical part. All were tested on real speech signals and the results are discussed at the end of the thesis.
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Warning system to keep the vehicle in the lane
Fendrich, Vítězslav ; Říha, Kamil (referee) ; Poměnková, Jitka (advisor)
This thesis adresses designing a device that detects lane departure of a vehicle via a video feed from a camera module. This device is intended to be attached onto the windshield of the vehicle. The initial part of the thesis will cover the current methods of lane departure detection through a video feed. In the following part the selection of suitable hardware, specifically the latest model of a Raspberry Pi, has been made. Afterwards a suitable container for the aforementioned hardware has been designed and created using a 3D printer. Subsequently an appropriate LDWS algorithm is chosen and designed. In the next part, the range and parameters of a testing database through which the proper functionality of the device will be tested on are chosen. The final part of the thesis contains evaluation of the success rate of detection via the acquired database.
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Optimal methods for sparse data exchange in sensor networks
Valová, Alena ; Poměnková, Jitka (referee) ; Rajmic, Pavel (advisor)
This thesis is focused on object tracking by a decentralized sensor network using fusion center-based and consensus-based distributed particle filters. The model includes clutter as well as missed detections of the object. The approach uses sparsity of global likelihood function, which, by means of appropriate sparse approximation and the suitable dictionaty selection can significantly reduce communication requirements in the decentralized sensor network. The master's thesis contains a design of exchange methods of sparse data in the sensor network and a comparison of the proposed methods in terms of accuracy and energy requirements.
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Analysis and comparison of ROC curves of audio signals
Pospíšil, Lukáš ; Staněk, Miroslav (referee) ; Poměnková, Jitka (advisor)
This thesis deals with oportunity of ROC curve usage in the description of methods that work with sound signals. Specifically, it focuses on ways of detecting of stress in speech signals. The detection itselfs is done in a range of frequencies of the sound signal. There is also a classifier designed using ROC curves that decides whether the input signal is stressed or not. The output of this thesis are findings gathered from analyses and also some recommendation based on those analyses.
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Evaluation of classification efficiency using ROC cruves
Dluhý, Vojtěch ; Říha, Kamil (referee) ; Poměnková, Jitka (advisor)
This bachelor thesis is focused on work eith the ROC curves. Introduces the reader with ROC curves and their use to analyzing signals and basic priciples of spectral estimation and getting an AUC for ROC curve. Also shows an algorithm for detecting sound of siren in record using a simple algorithm and evaluation of various jamming sound of sirens by displaying the ROC curves, supplemented by calculation and comparing the areas under these curves (AUC). The algorithm is written in a development enviroment Matlab.
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Evaluation of classification efficiency using ROC cruves
Dluhý, Vojtěch ; Sigmund, Milan (referee) ; Poměnková, Jitka (advisor)
This semestral thesis is focused on work eith the ROC curves. Introduces the reader with ROC curves and their use to analyzing signals. Also shows an algorithm for detecting sound of siren in record using a simple algorithm and evaluation of various jamming sound of sirens by displaying the ROC curves, supplemented by calculation and comparing the areas under these curves (AUC). The algorithm is written in a development enviroment Matlab.
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Identification of significant spectral components in speach signal in stress
Dulesov, Egor ; Tučková, Jana (referee) ; Poměnková, Jitka (advisor)
The aim of this master’s thesis is to learn the problem of analysis and identification of significant spectral components in speech signal. Based on learning a special literature chooses the suitable methods of spectrum estimate. Does learning the literature in specification of testing of spectral components significate. Makes a procedure for identification of chosen speech formants. Does this procedure for audio signals both of in stress and in normal state. Estimates the results, compares efficiency of chosen methods and determine threshold for chosen formant of analyzed stress signal. States the recommendations for speech spectral analysis in stress situation.
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Filtration of time series
Pinkava, Jan ; Poměnková, Jitka (referee) ; Maršálek, Roman (advisor)
Thesis is aimed at describing the concepts and basic principles in the economy in gross domestic product. Furthermore it deals with the description of time series, their types, characteristics and the basic classification. A decomposition of time series into thein components is indicated. Another part is a basic description of the most commonly used economic filters - Hodrick-Prescott and Baxter-King. The Christiano-Fitzgerald and frequency-selective filter for short length time series have been practically implemented in MATLAB. The rest of the thesis deals with the application of above mentioned filters to data of Czech Republic, European Union, USA and selected EU countries. Moreover, the correlation between spectral components of the data for selected countries is investigated. KEYWORDS
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Time-frequency analysis of Czech republic gross domestic product
Tráge, David ; Poměnková, Jitka (referee) ; Maršálek, Roman (advisor)
The aim of this master's thesis is to get familier with problematic and concepts of econometrics (GDP, investment, usage and others). We see into used data mainly their characters and expectations and we discuss possibilities of frequention and time-frequention analysis of these data by Fourier and Wavelet transform. Data of quarter development of gross domestic product in Czech Republic, EU and USA will be analysed by the help of programm MATLAB. Data will be filtered by three ekonomic filters: Hodrick-Prescott, Baxter-King and Christiano-Fitzgerald filters. The aim is to find cyclic elements in developments of GDPs and to suggest an optimal type of analysis.
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