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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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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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Detection of the Cars Approaching the Crossroad
Hopjan, Tomáš ; Peringer, Petr (referee) ; Rozman, Jaroslav (advisor)
This project deals with monitoring cars approaching the crossroads. Describes various methods of detection and discussing their problems. Primary goal is surveillance during the day in different weather conditions, but method of detection cars during the night and low light is also introduced. The most widely used algorithms are implemented using the OpenCV library. Important part is testing different algorithms and also variety of lighting conditions, camera locations and settings.
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Object Tracking in Video Sequences
Mlích, Jozef ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
In this master thesis, image processing methods and methods for statistical modeling of motion are presented. First, description methods of image processing, such as background subtraction method used for object detection, are presented. Next, description of morphological operations, such as dilatation and erosion, is done. Finally, methods for statistical modeling, such as Kalman filter and particle filters, are shown.
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Optimization of Aircraft Tracker Parameters
Samek, Michal ; Vlk, Jan (referee) ; Smrž, Pavel (advisor)
Diplomová práce se zabývá optimalizací systému pro sledování letadel, využívaného pro řízení letového provozu. Je popsána metodika vyhodnocování přesnosti sledovacího systému a přehled relevantních algoritmů pro sledování objektů. Dále jsou navrženy tři přístupy k řešení problému. První se pokouší identifikovat parametry filtrovacích algoritmů pomocí algoritmu Expectation-Maximisation, implementací metody maximální věrohodnosti. Druhý přístup je založen na prostých odhadech parametrů normálního rozložení z naměřených a referenčních dat. Nakonec je zkoumána možnost řešení pomocí optimalizačního algoritmu Evoluční strategie. Závěrečné vyhodnocení ukazuje, že třetí přístup je pro daný problém nejvhodnější.
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Mobile Robot Navigation
Goldmann, Tomáš ; Luža, Radim (referee) ; Orság, Filip (advisor)
When we look at the eld of robotics we nd that exist a lot of types of robots. Some of tham use location navigation and global navigation for their work. This work aims to map options of location navigation and description of basic technique which used. Especially, we will deal with algorithms which work with optical sensors, for example camera, stereocamera or laser which scan medium. Practise section this work is focused on the proposal and implementacion algorithm which working with local navigation for robot's return to the starting position. All this work is connecting with tracked robot which formed in the framework one of project realization at Faculty of information technology.
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Attitude Estimation of Multicopters
Baránek, Radek ; Jalovecký, Rudolf (referee) ; Krejsa,, Jiří (referee) ; Šolc, František (advisor)
This dissertation deals with attitude estimation of multicopters. Mainly the use of multicopter dynamic model in order to gain accuracy is investigated. It shows that the usage of multicopter dynamic model brings advantage contrary to other known algorithms for attitude estimation such as GPS/INS or complementary filter. Besides others one goal is to study the possibilities to estimate the parameters of dynamic model on-line. Further the influence of wind speed to estimation accuracy is also investigated. The algorithms are based on a nonlinear Kalman filter. The use of dynamic model of multicopters reveals the possibility of estimating attitude with bounded error even without periodic measurement of absolute position. One of the results of the dissertation is a new algorithm which does not require information about the thrust of multicopter propellers.
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Application of SLAM algorithms for 4WS vehicle
Najman, Jan ; Krejsa, Jiří (referee) ; Grepl, Robert (advisor)
This paper deals with the application of SLAM algorithms on experimental four wheel vehicle Car4. The first part shows the basic functioning of SLAM including a description of the extended Kalman filter, which is one of its main components. Then there is a brief list of software tools available to solve this problem in the environment of MATLAB and an overview of sensors used in this work. The second part presents methodology and results of the testing of individual sensors and their combinations to calculate odometry and scan the surrounding space. It also shows the process of applying SLAM algorithms on Car4 vehicle using the selected sensors and the results of testing of the entire system in practice.
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Development of algorithms state estimation of experimental vehicle
Lamberský, Vojtěch ; Krejsa, Jiří (referee) ; Grepl, Robert (advisor)
This thesis deals with the filter algorithm design, implementing mathematical model to improve algorithm performance. Designed algorithms are implemented in a control unit of the experimental vehicle (filters signal used in the closed-loop controller). The improvement of the position estimation using Kalman Filter is demonstrated on the experimental vehicle. In the next part the design process of algorithm developing for dsPIC microcontroller using Matlab is described.
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moving objects tracking
Bradáč, František ; Gogol, František (referee) ; Richter, Miloslav (advisor)
The thesis deals with founding and tracking of moving objects inside of visual field and prediction of their future position. The created methods combine few approaches for solution this problem. First, the most probable of the static part of the observed scene is created. Then this model is used to detect moving objects. The correspondence of objects between two consecutive pictures is performed by analyzing of motion of these objects. For analyzing of motion of the objects optical flow is used. Prediction of the future position is performed by Kalman filter. Providing suitable condition these methods are able to track the moving objects even if these objects are passing closely or colliding. The methods are implemented in language C++ and their functionality was verified by sample with scanned non static scene.
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