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I Offer/Seek Local Help. How to Connect These People Effectively and Safely?
Kohútová, Alena ; Veľas, Martin (referee) ; Beran, Vítězslav (advisor)
The aim of this bachelor thesis is to design a system that will connect people seeking help with those who need it, focusing on the effectiveness of use and motivation of users using gamification techniques. The system allows you to add contribution, start user collaboration, add ratings to other users and more. The resulting web system is implemented using modern web design techniques. The output of the work is an implemented prototype, which is evaluated by user testing.
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3D Mapping from Sparse LiDAR Data
Veľas, Martin ; Hofierka,, Jaroslav (referee) ; Kaartinen,, Harri (referee) ; Herout, Adam (advisor)
Tato práce se zabývá návrhem nových algoritmů pro zpracování řídkých 3D dat senzorů LiDAR, včetně kompletního návrhu batohovího mobilního mapovacího řešení. Tento výzkum byl motivován potřebou takových řešení v oblasti geodézie, mobilního průzkumu a výstavby. Nejprve je prezentován iterační algoritmus pro spolehlivou registraci mračen bodů a odhad odometrie z měření 3D LiDARu. Problém řídkosti a velikosti těchto dat je řešen pomocí náhodného vzorkování pomocí Collar Line Segments (CLS). Vyhodnocení na standardní datové sadě KITTI ukázalo vynikající přesnost oproti známému algoritmu General ICP. Konvoluční neuronové sítě hrají důležitou roli ve druhé metodě odhadu odometrie, která zpracovává kódovaná data LiDARu do 2D matic. Metoda je schopna online výkonu, zatímco je zachována přesnost, když požadujeme pouze parametry posunu. To může být užitečné v situacích, kdy je vyžadován online náhled mapování a parametry rotace mohou být spolehlivě poskytnuty např. senzorem IMU. Na základě algoritmu CLS bylo navrženo a implementováno batohové mobilní mapovací řešení 4RECON. S využitím kalibrovaného a synchronizovaného páru LiDARů Velodyne a s nasazením řešení GNSS/INS s duální anténou, byl vyvinut univerzální systém poskytující přesné 3D modelování malých vnitřních i velkých otevřených prostředí. Naše hodnocení prokázalo, že požadavky stanovené pro tento systém byly splněny -- relativní přesnost do $5$~cm a průměrná chyba georeferencí pod $12$~cm. Poslední stránky obsahují popis a vyhodnocení další metody založené na konvolučních neuronových sítích -- navržených pro segmentaci země v mračnech bodů 3D LiDARu. Tato metoda překonala současný stav techniky v této oblasti a představuje způsob, jakým může být sémantická informace vložena do 3D laserových dat.
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Object Detection in the Laser Scans Using Convolutional Neural Networks
Zelenák, Michal ; Kodym, Oldřich (referee) ; Veľas, Martin (advisor)
This work is focused on road segmentation in laser scans, using a convolutional neural network. To achieve this goal, which will find application in the field of road maintenance, convolutional neural networks have been used for their flexibility and speed. The work brings implementation and modifications of the existing method, which solves the problem by using a fully connected convolutional neural network. Used modifications include, for example using of various parameters for the loss function, the use of a different number of classes in the network model and dataset. The effect of the modification was experimentally verified and the accuracy of 96.12%, and the value for F-measure 95.02% were achieved.
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Navigation Using Deep Convolutional Networks
Skácel, Dalibor ; Veľas, Martin (referee) ; Hradiš, Michal (advisor)
This thesis studies navigation and autonomous driving using convolutional neural networks. It presents main approaches to this problem used in literature. It describes theory of neural networks and imitation and reinforcement learning. It also describes tools and methods suitable for a driving system. There are two simulation driving models created using learning algorithms DAGGER and DDPG. The models are then tested in car racing simulator TORCS.
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Road Detection for Autonomous Car
Komora, Matúš ; Veľas, Martin (referee) ; Španěl, Michal (advisor)
This thesis deals with detection of the road adjacent to an autonomous vehicle. The road is recognition is based on the Velodyne LiDAR laser radar data. An existing solution is used and extended by machine learning - a Support Vector Machine with online learning. The thesis evaluates the existing solution and the new one using a KITTI dataset. The reliability of the road recognition is then computed using F-measure.
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Calibration of Robotic Workspace
Uhlíř, Jan ; Veľas, Martin (referee) ; Kapinus, Michal (advisor)
This work is concerned by the issue of calibrating a robotic workplace, including the localization of a calibration object for the purpose of calibrating a 2D or 3D camera, a robotic arm and a scene of robotic workplace. At first, the problems related to the calibration of the aforementioned elements were studied. Further, an analysis of suitable methods for performing these calibrations was performed. The result of this work is application of ROS robotic system providing methods for three different types of calibration programs, whose functionality is experimentally verified at the end of this work.
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Street View Mapping Using the Sensory Mobile Platform
Győri, Adam ; Kapinus, Michal (referee) ; Veľas, Martin (advisor)
The aim of this bachelor's thesis is to develop a web application that facilitates viewing of panoramatic photographies while having an optional map background. Application works for usage of surveyors, mainly for pasportization of buildings and grounds. Main aim of the application is to simplify inspection of recorded image data. Solution consists of visual display of view and creating of switchable map background.
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3D Educational Application Using the Depth Sensors
Zubrik, Tomáš ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This work deals with the creation of an interactive learning system that uses depth sensor and projector to render an interactive topographic map on the top of the sand surface. Our solution is based on the existing application AR Sandbox. Aditionally to the visualization elevation, the application allows the user to model the terrain model interactivelly, while guiding him by color distinguishment to create model correctly. We have developed an extension that allows the user to choose any part of the Earth's surface to create its model. The solution utilizes the full potential of the original application and offers the user an engaging experience in modeling the landforms or river basins. The result of this work is an operational system, which is helpful for gaining the knowledge in the field of topography and hydrology. User testing was evaluated using a UEQ questionnaire and has proven the usability, while achieving average score of 1.2, which is rated above-average on the UEQ scale.
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Cloud Solution for 3D Models Processing
Klemens, Jakub ; Veľas, Martin (referee) ; Španěl, Michal (advisor)
This thesis deals with the possibilities of processing 3D models in cloud applications. A C++ library called Cloud3D has been designed and implemented. The resulting library is used to quickly create client-server applications. The library is divided into three separate parts: Client, Service Provider and Load Balancer. The service provider runs in the cloud and provides 3D model processing services to client applications. The biggest advantage of Cloud3D is the ease of creating new applications with its help. Other benefits include scalability, assured implementation of look-a-side Load Balancer, and security ensured by the use of SSL certification.
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Planar Object Measurement in Image
Mlýnek, Přemysl ; Veľas, Martin (referee) ; Beran, Vítězslav (advisor)
The aim of this work is to measure furniture doors using image processing and calculating the price of new doors from measured dimensions. The work is solved using OpenCV library and Python programming language. The core of the work is based on the FloodFill algorithm and Hough transforms. The graphical user interface is solved using the PyQt library. When obtaining the measurements of the furniture door, the following procedure is used - acquisition of a data set, imagine preprocessing, object segmentation, object classification, measurement of individual objects, output of measurement results and output price calculation. I have created a solution in the form of a desktop application that accepts an image at the input and outputs the measured dimensions along with the price of the new door. I managed to achieve an average deviation of 6 mm from real dimensions. This work has helped me understand the basics of image processing. An ordinary user of the application will be able to estimate the price of new furniture doors just based on a photo.
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