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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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Augmented Reality based on Planar Object and Local Image Features
Bárta, Milan ; Chrápek, David (referee) ; Beran, Vítězslav (advisor)
This bachelor's thesis deals with creating an augmented reality application which allows mapping of planar object and camera position localization with possibility of rendering additional information into the picture. Procedures used in image stitching process using local features are described in detail. These are the fundamental techniques for creating augmented reality applications. The thesis focuses on designing and implementation of such an application.
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The idnetification of the objects in the imege
Zavalina, Viktoriia ; Fliegel, Karel (referee) ; Boleček, Libor (advisor)
Master´s thesis deals with methods of objects detection in the image. It contains theoretical, practical and experimental parts. Theoretical part describes image representation, the preprocessing image methods, and methods of detection and identification of objects. The practical part contains a description of the created programs and algorithms which were used in the programs. Application was created in MATLAB. The application offers intuitive graphical user interface and three different methods for the detection and identification of objects in an image. The experimental part contains a test results for an implemented program.
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Merging and Correction of Photos
Trčka, Jan ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
The aim of this work is to design and implement an application using an OpenCV library. This paper describes issues of correct photo merging, attempts to eliminate defects which were created in process of taking these photos and which may occur in the actual merging process.
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Automatic Photography Categorization
Matuszek, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deal with choosing methods, design and implementation of application, which is able of automatic categorization photos based on its content into predetermined groups. Main steps of categorization are described in greater detail. Finding and description of interesting points in image is implemented using SURF, creation of visual dictionary by k-means, mapping on the words through kd-tree structure. Own evaluation is made for categorization. It is described, how the selected steps were implemented with OpenCV and Qt libraries. And the results of runs of application with different settings are shown. And efforts to improve outcome, when the application can categorize right, but success is variable.
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Automatic Photography Categorization
Veľas, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to create an application, which is would be able to achieve sufficient precision and computation speed of categorization. Basic solution involves detection of interesting points, extraction of feature vectors, creation of visual codebook by clustering, using k-means algorithm and representing visual codebook by k-dimensional tree. Photography is represented by bag of words - histogram of presence of visual words in a particular photo. Support vector machines (SVM) was used in role of classifier. Afterwards the basic solution is enhanced by dividing picture into cells, which are processed separately, computing color correlograms for advanced image description, extraction of feature vectors in opponent color space and soft assignment of visual words to extracted feature vectors. The end of this thesis concerns to experiments of of above mentioned techniques and evaluation of the results of image categorization on their usage.
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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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Merging of Images and Video Sequences
Krym, David ; Seeman, Michal (referee) ; Zemčík, Pavel (advisor)
This bachelor thesis deals with image and video sequence frames stitching when the camera undergoes a pure rotation. It involves design and implementation of application with focus on quality and performance. Modern techniques and algorithms are used, such as SURF, ORB, k-nearest neighbors and bundle adjustment. The application is able to create a panoramic images automatically without any assumptions about the scene or camera.
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Automorphing of the Image Pairs
Čermák, Pavel ; Nečas, Ondřej (referee) ; Beran, Vítězslav (advisor)
This thesis I deal with creating automorphing between source and destination image. The thesis describes existing methods and algorithms for creating morphing. The thesis focuses on the design and implementation methods for creating automorphing. For this purpose it is necessary to detect significant points in the image, find correspondence of to these points and create your own morphing.
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