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Object tracking in video
Boszorád, Matej ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with the issue of tracking multiple objects in a video, specifically focusing on non-learning algorithms. The first chapter represents the theoretical part of the thesis, in which some of the often used tracking methods are described, such as mean-shift, scale-invariant object transformation, Kalman filter, particle filter and Gabor wavelet transformation. These algorithms are broken down by properties they use for proper tracking. The chapter also contains section assignment problem, which is mainly concerned with Hungarian algorithm. The next part describes options of merging multiple tracking methods that are broken down by construction type into parallel, cascade, weighted and discriminatory with example for each one. Moreover there is described adaptability of the tracking system. Bellow are described problems which may occur during tracking and possible solutions to them. This section consists of a solution of image noise, changes in illumination, appearance and extinction of an object, focusing mainly on solving the problem of object occlusion. Within the practical part is created algorithm composed of different types of tracking, the results of which are then compared with selected tracking systems from the multiple object tracking benchmark. The practical part includes the tools used and the explanation of the design, in which the main classes and methods used for the tracking are explained. Besides that, this section describes parallel merging and tracking adaptability . The results of the thesis contain a comparison of the use of tracking techniques separately and together. To compare the results, videos for pedestrian tracking and face tracking were used. This thesis was based on the assumption that merging multiple monitoring systems will help with the improvement of the tracking, which was confirmed by the results.
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Robot for Robotour 2012
Vass, Robert ; Luža, Radim (referee) ; Rozman, Jaroslav (advisor)
The aim of this article is the theoretical analysis, proposal and implementation of a method for the operation of an autonomous robot for Robotour 2012 with the help of camera and sensor usage. Key issues to be faced are the computer vision, robot sensing uncertainty and the localization problem. Firstly, road extraction is achieved by using colour segmentation. Secondly, for the combination of information of different uncertain sources, Kalman Filter is proposed. Finally, the information received by the camera which serves for the building of an occupancy grid map corrected by sensors is de facto the representation of environment for the robot.
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Moving object tracking
Sehnoutka, Martin ; Horák, Karel (referee) ; Richter, Miloslav (advisor)
This thesis deals with application of computer vision for purposes of object tracking in a video record. In first part of this document, algorithms of computer vision are described theoretically. Next part contains design of map of movement in a scene. All these procedures were used during implementation of program for tracking of moving objects. Discussion of program functionality is in the last chapter.
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Evolutionary Design of Filters for Signal Processing
Dobiš, Tomáš ; Hrbáček, Radek (referee) ; Dobai, Roland (advisor)
Kalman filter is used for signal filtering dependent on filter configuration and prediction of values. It's configuration is difficult and requires experiences of mathematician. This thesis deals with implementation of method for signal processing with use of Cartesian genetic programming, which advantage includes the automated configuration of filter. Final method is compared on multiple testing examples with Kalman filter. From results we can infer, that implemented method works comparatively efficient on periodic and exponential signal inputs, and works significantly better on constant signal inputs than Kalman filter.
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Network Anomaly Detection
Pšorn, Daniel ; Puš, Viktor (referee) ; Kořenek, Jan (advisor)
This master thesis deals with detecting anomalies methods in network traffic. First of all this thesis analyzes the basic concepts of anomaly detection and already using technology. Next, there are also described in more detail three methods for anomalies search and some types of anomalies. In the second part of this thesis there is described implementation of all three methods and there are presented the results of experimentation using real data.
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Multifunction data acquisition, measurement and control device
Trávníček, Ivo ; Vlachý, David (referee) ; Grepl, Robert (advisor)
The thesis deals with and tests the Multifunction data acquisition, measurement and control device. The unit is based on the microcontroller ATmega, which was programmed in the language C. The unit contains functions for the measurement of physical quantify, filtering record, regulation of the dynamic systems and communication with PC. Configuration of the unit is real-time in special software created in the language Matlab or by a terminal. The purpose of the unit is controlling a DC motor by the PID regulator, long-term measurement of temperature or measurement of acceleration by an accelerometer.
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Analysis of impact of noise in recordings on the automated detection of hypokinetic dysarthria
Havelková, Nikola ; Galáž, Zoltán (referee) ; Kováč, Daniel (advisor)
This thesis deals with the automated detection of hypokinetic dysarthria by analysing the influence of noise present in recordings. Appropriate single-channel methods, specifically the spectral subtraction and Kalman filter, are selected and implemented in the MATLAB R2022a to enhance speech. These methods are also used for noise-free recordings, to which additive white noise was added. Afterwards, the effectiveness of these methods is objectively evaluated by using signal-to-noise ratio values. After enhancing of speech, interferences are extracted from the recordings. The effect of the presence of noise, as well as its subsequent suppression by individual methods, is then evaluated by statistical analysis, specifically using the Kruskal-Wallis test and the post hoc Dunn’s test. The probability of distributing parameters of clean, noisy and enhanced recordings, for which the effect of noise is significant, according to statistical tests, are plotted using violin and box graphs. Finally, the classification was done by logistic regression with the help of machine learning, where the effect of the presence of noise and subsequent speech enhancement on automated detection of hypokinetic dysarthria was described according to the area values under the ROC curve.
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Multi Object Class Learning and Detection in Image
Chrápek, David ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.
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Modern Flight Control System Design and Evaluation
Vlk, Jan ; Holzapfel, Florian (referee) ; Rzucidlo, Pawel (referee) ; Mathan, Santosh (referee) ; Chudý, Peter (advisor)
Tato práce je zaměřena na výzkum moderních metod automatického řízení letu a jejich ověření s ohledem na současný stav poznání a budoucí využití bezpilotních letadlových systémů. Práce představuje proces návrhu automatického systému řízení letu s důrazem na přístupy z oblasti návrhu založeného na modelování (Model-Based Design). Nedílnou součástí tohoto procesu je tvorba matematického modelu letounu, který byl využit k syntéze zákonů řízení a k vytvoření simulačního rámce pro evaluaci stability a kvality regulace automatického systému řízení letu. Jádro této práce se věnuje syntéze zákonů řízení založených na unikátní kombinaci teorie optimálního a adaptivního řízení. Zkoumané zákony řízení byly integrovány do digitálního systému řízení letu, jenž umožňuje vysoce přesné automatické létání. Závěrečná část práce se zabývá ověřením a analýzou navrženého systému řízení letu a je rozdělena do 3 fází. První fáze ověření obsahuje evaluaci robustnosti a analyzuje stabilitu a robustnost navrženého systému řízení letu ve frekvenční oblasti. Druhá fáze, evaluace kvality regulace, probíhala v rámci počítačových simulací s využitím vytvořených matematických modelů v časové oblasti. V poslední fázi ověření došlo k integraci navrženého systému řízení letu do experimentálního letounu, sloužícího jako testovací platforma pro budoucí bezpilotní letadlové systémy a jeho evaluaci v rámci série letových experimentů.
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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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