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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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3D Model of a Room Using Kinect
Zemek, Martin ; Veľas, Martin (referee) ; Španěl, Michal (advisor)
This thesis is about finding significant planar surfaces in point cloud and their conversion to polygons. Which is important step for making a 3D model of a room. Input is point cloud, which was recorded by Kinect v2 sensor. Tool for capturing one snapshot from Kinect is included in this thesis. For recording more detailed point cloud is needed external program. Some of the programs are mentioned further in this thesis. For plane detection is used RANSAC. Inliers are divided using Euclidean Cluster Extraction. These clusters are converted to polygon using convex or concave hull. Application is capable of working with one snapshot or bigger point cloud assembled by registration of particular snapshots and detect primary and secondary planar surfaces. For the largest plane points can be prepared for creation of a texture and dimensions of this plan can be printed in CLI.
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Moving Object Detection in the Environment of Mobile Robot
Dorotovič, Viktor ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This work's aim is movement detection in the environment of a robot, that may move itself. A 2D occupancy grid representation is used, containing only the currently visible environment, without filtering in time. Motion detection is based on a grid-based particle filter introduced by Tanzmeister et al. in Grid-based Mapping and Tracking in Dynamic Environments using a Uniform Evidential Environment Representation. The system was implemented in the Robot Operating System, which allows for re-use of modules which the solution is composed of. The KITTI Visual Odometry dataset was chosen as a source~of LiDAR data for experiments, along with ground-truth pose information. Ground segmentation based on Loopy Belief Propagation was used to filter the point clouds. The implemeted motion detector is able to distiguish between static and dynamic vehicles in this dataset. Further tests in a simulated environment have shown some shortcomings in the detection of large continuous moving objects.
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Deep Learning for Image Classification
Ziková, Jana ; Veľas, Martin (referee) ; Hradiš, Michal (advisor)
This bachelor thesis deals with electronic commerce website products classification using product's photographs. For this purpose we use already implemented models of deep convolutional neural networks. Tho goal of this theses is to design experiments that will lead to the best possible results in product images classification.
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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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Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
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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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Mobile App for Sharing Information about Presence in a Location
Vlk, Tomáš ; Veľas, Martin (referee) ; Herout, Adam (advisor)
The aim of this work is to create a user-friendly mobile application for Android that will make it easier to share ones's location while keeping their privacy. Instead of the GPS coordinates of the current location, the application only shares the information about the user's presence at the place. For easier sharing, it also offers automatic detection of the presence at a specific place. The result of this work is a application with a user interface that respects the Material Design, which makes it possible to determine the device's presence at a place with a radius greater than 50 meters, but there is no active polling. The application which has been created does not need to be run at all (or any of its background services) and it can detect the device's presence at a specific place and receive messages from other devices. The biggest advantage of this approach is very low energy consumption in contrast to other solutions.
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Vehicle for Small and Remote Space Mapping
Koupý, Pavel ; Veľas, Martin (referee) ; Beran, Vítězslav (advisor)
This work describes process of making a robotic vehicle for remote mapping of small indoor spaces and areas. Such process involves design and construction, selection and connection of used electronic parts and implementation of interface witch wil provide set of tools as remote control, camera stream or autonomous space search.
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Localisation of Mobile Robot in the Environment
Němec, Lukáš ; Hradiš, Michal (referee) ; Veľas, Martin (advisor)
This paper addresses the problem of mobile robot localization based on current 2D and 3D data and previous records. Focusing on practical loop detection in the trajectory of a robot. The objective of this work was to evaluate current methods of image processing and depth data for issues of localization in environment. This work uses Bag of Words for 2D data and environment of point cloud with Viewpoint Feature Histogram for 3D data. Designed system was implemented and evaluated.
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