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Embedded display recognition
Novotný, Václav ; Janáková, Ilona (referee) ; Honec, Peter (advisor)
This master thesis deals with usage of machine learning methods in computer vision for classification of unknown images. The first part contains research of available machine learning methods, their limitations and also their suitability for this task. The second part describes the processes of creating training and testing gallery. In the practical part, the solution for the problem is proposed and later realised and implemented. Proper testing and evaluation of resulting system is conducted.
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Object Instance Search in Image Dataset
Medvec, Juraj ; Brejcha, Jan (referee) ; Beran, Vítězslav (advisor)
This project is focused on the selected techniques for image searching. In the introduction are presented all existing solutions, which are used in daily use. The other chapters are focused on creating resulting framework. On the end is introduced the demo application, which is using the framework for searching books by front page image.
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Registration of Photos to 3D Model
Deák, Jaromír ; Brejcha, Jan (referee) ; Čadík, Martin (advisor)
This work refers existing solutions and options for the task registration of photos to 3D model based on the previous knowledge of the geographic position of the camera. The contribution of the work are new ways and possibilities of the solution with the usage of graph algorithms. In this area, the work interests are useful points of interest detection in input data, a construction of graphs and graph matching possibilities.
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The Impact of Image Resolution on the Precision of Content-based Retrieval
Navrátil, Lukáš ; Lokoč, Jakub (advisor) ; Skopal, Tomáš (referee)
This thesis is focused on comparing methods for similarity image retrieval. Common techniques and testing sets are introduced. The testing sets are there to measure the accuracy of the searching systems based on similarity image retrieval. Measurements are done on those models which are implemented on the basis of presented techniques. These measurements examine their results depending on the input data, used components and parameters settings, especially the impact of image resolution on the retrieval precision is examined. These results are analysed and the models are compared. Powered by TCPDF (www.tcpdf.org)
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3D model
Sládeček, Martin ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
This paper concerns the task three-dimensional scene using image sequence obtained with an ordinry camera. First portion of this thesis outlines the principles used in solving of the task, the second chapter describes a reconstucion algorithm and it's implementation in the Python programming language. The output of this program is demonstrated on several selected scenes. Final remarks discuss the quality of resulting models, shortcomings of the program and possible improvements.
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Machine Learning Concepts for Categorization of Objects in Images
Hubený, Marek ; Honec, Peter (referee) ; Horák, Karel (advisor)
This work is focused on objects and scenes recognition using machine learning and computer vision tools. Before the solution of this problem has been studied basic phases of the machine learning concept and statistical models with accent on their division into discriminative and generative method. Further, the Bag-of-words method and its modification have been investigated and described. In the practical part of this work, the implementation of the Bag-of-words method with the SVM classifier was created in the Matlab environment and the model was tested on various sets of publicly available images.
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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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Image objects detection based on the feature points matching
Trávníček, Vojtěch ; Macíček, Ondřej (referee) ; Harabiš, Vratislav (advisor)
This paper is concerned in branch of computer vision. Methods for extracting feature points are presented as tools for image comparison and finding objects in images. Four methods are metioned which are compared with respect to their effectiveness and utilization. Algorythms SIFT and SURF are described as a state-of-the-arts. This paper also mentions methods for describing feature points and their comparison. Testing images are inserted as a tool for first testing of implemented algorythm. Finally, the implemented method SURF is described and tested with respect to several most relevant parameters.
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Automatic calculation of relative orientation of two cameras
Adámek, Daniel ; Nováček, Petr (referee) ; Klečka, Jan (advisor)
To determine a relative orientation of two cameras, it is necessary to understand wide range of fields. Therefore, this thesis showes principles of basic methods of detection and description of keypoints in an image as well as methods of matching these keypoints. The paper also provides brief summary of epipolar geometry and linear triangulation. C++ implementation of presented theory was proposed and its disadvantages were discussed.
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Region Detectors and Descriptors in Image
Žilka, Filip ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master’s thesis deals with an important part of computer vision field. Main focus of this thesis is on feature detectors and descriptors in an image. Throughout the thesis the simplest feature detectors like Moravec detector will be presented, building up to more complex detectors like MSER or FAST. The purpose of feature descriptors is in a mathematical description of these points. We begin with the oldest ones like SIFT and move on to newest and best performing descriptors like FREAK or ORB. The major objective of the thesis is comparison of presented methods on licence plate localization task.
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