National Repository of Grey Literature 31 records found  beginprevious22 - 31  jump to record: Search took 0.00 seconds. 
Traffic Monitoring from Aerial Video Data
Babinec, Adam ; Orság, Filip (referee) ; Rozman, Jaroslav (advisor)
This thesis proposes a system for extraction of vehicle trajectories from aerial video data for traffic analysis. The system is designed to analyse video sequence of a single traffic scene captured by an action camera mounted on an arbitrary UAV flying at the altitudes of approximately 150 m. Each video frame is geo-registered using visual correspondence of extracted ORB features. For the detection of vehicles, MB-LBP classifier cascade is deployed, with additional step of pre-filtering of detection candidates based on movement and scene context. Multi-object tracking is achieved by Bayesian bootstrap filter with an aid of the detection algorithm. The performance of the system was evaluated on three extensively annotated datasets. The results show that on the average, 92% of all extracted trajectories are corresponding to the reality. The system is already being used in the research to aid the process of design and analysis of road infrastructures.
Navigation of mobile robots
Rozman, Jaroslav ; Matoušek,, Václav (referee) ; Šolc, František (referee) ; Zbořil, František (advisor)
Mobile robotics has been very discussed and wide spread topic recently.   This due to the development in the computer technology that allows us to create   better and more sophisticated robots. The goal of this effort is to create robots   that will be able to autonomously move in the chosen environment. To achieve this goal,   it is necessary for the robot to create the map of its environment, where   the motion planning will occur. Nowadays, the probabilistic algorithms based   on the SLAM algorithm are considered standard in the mapping in these times.   This Phd. thesis deals with the proposal of the motion planning of the robot with   stereocamera placed on the pan-and-tilt unit. The motion planning is designed with   regard to the use of algorithms, which will look for the significant features   in the pair of the images. With the use of the triangulation the map, or a model will be created.     The benefits of this work can be divided into three parts. In the first one the way   of marking the free area, where the robot will plan its motion, is described. The second part   describes the motion planning of the robot in this free area. It takes into account   the properties of the SLAM algorithm and it tries to plan the exploration in order to create   the most precise map. The motion of the pan-and-tilt unit is described in the third part.   It takes advantage of the fact that the robot can observe places that are in the different   directions than the robot moves. This allows us to observe much bigger space without   losing the information about the precision of the movements.
Robot Localization Using OpenStreet Map
Rajnoch, Zdeněk ; Veľas, Martin (referee) ; Rozman, Jaroslav (advisor)
Goal of this thesis is localization of mobile robot in OpenStreet map segment. Robot IMU, odometry and compass sensors are used for trajectory reconstruction, which is compared to reference GPS trajectory. Extended Monte Carlo localization and clusterization are used for robot localization. Software is implemented in C++ with ROS middleware.
Object Tracking in Video
Beťko, Peter ; Mlích, Jozef (referee) ; Herout, Adam (advisor)
This bachelor's thesis is dealing with implementation and testing of algorithms used for object tracking in video, based on the principle of Particle filter. Their features are compared and discused using a tool, that objectively evaluates the accuracy of tracking. Other topics are dynamic adaptation on actual scene characteristics and recovery from object overlay.
Object Tracking in Video Using CUDA
Schery, Miroslav ; Polok, Lukáš (referee) ; Herout, Adam (advisor)
This bachelors thesis is focused on implementation of particle filter algorithm in CUDA technology for the purpose of computation acceleration. It describes object tracking methods in video and is especialy aimed at particle filter. It also describes the CUDA architecture. Implementation and optimalization techniques used in application are explained. The work ends with performing speed tests and the tracking ability of the algorithm is verified on various videos.
Detection and Tracking of Small Moving Objects
Záděra, David ; Mlích, Jozef (referee) ; Juránek, Roman (advisor)
This thesis summarizes and describes the methods for detecting and tracking moving objects in video. The detection methods discussed in the working are background subtraction, segmentation and detection methods using classifiers. From tracking methods are presented Kalman filter, TLD method and particle filter, which is described in detail in a separate chapter. Particle filter is a tracking method that calculates a new estimate of the state of the object based on a set of particles. These particles are defined by their positions and weights. For each next state are these values iteratively updated by measurment and resampling. From the acquired knowledge and expertise has been created a program that demonstrates the activity of the particle filter. This program is part of the DVD, where are also the samples and test results.
Moving Object Detection in Video Using CUDA
Čermák, Michal ; Havel, Jiří (referee) ; Herout, Adam (advisor)
This thesis deals with model-based approach to 3D tracking from monocular video. The 3D model pose dynamically estimated through minimization of objective function by particle filter. Objective function is based on rendered scene to real video similarity.
Parametrization of Image Point Neighborhood
Zamazal, Zdeněk ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This master thesis is focused on parametrization of image point neighborhood. Some methods for point localization and point descriptors are described and summarized. Gabor filter is described in detail. The practical part of thesis is chiefly concerned with particle filter tracking system. The weight of each particle is determined by the Gabor filter.
Personal Navigation Based on Wireless Networks and Inertial Sensors
Kaňa, Zdeněk ; Raida, Zbyněk (referee) ; Soták,, Miloš (referee) ; Bradáč, Zdeněk (advisor)
Tato práce se zaměřuje na vývoj navigačního algoritmu pro systémy vhodné k lokalizaci osob v budovách a městských prostorech. Vzhledem k požadovaným nízkým nákladům na výsledný navigační systém byla uvažována integrace levných inerciálních senzorů a určování vzdálenosti na základě měření v bezdrátových sítích. Dále bylo předpokládáno, že bezdrátová síť bude určena k jiným účelům (např: měření a regulace), než lokalizace, proto bylo použito měření síly bezdrátového signálu. Kvůli snížení značné nepřesnosti této metody, byla navrhnuta technika mapování ztrát v bezdrátovém kanálu. Nejprve jsou shrnuty různé modely senzorů a prostředí a ty nejvhodnější jsou poté vybrány. Jejich efektivní a nové využití v navigační úloze a vhodná fůze všech dostupných informací jsou hlavní cíle této práce.

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