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Efficiency of deep convolutional neural networks on an elementary classification task
Prax, Jan ; Dobrovský, Ladislav (referee) ; Škrabánek, Pavel (advisor)
In this thesis deep convolutional neural networks models and feature descriptor models are compared. Feature descriptors are paired with suitable chosen classifier. These models are a part of machine learning therefore machine learning types are described in this thesis. Further these chosen models are described, and their basics and problems are explained. Hardware and software used for tests is listed and then test results and results summary is listed. Then comparison based on the validation accuracy and training time of these said models is done.
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Stitching of Retinal Images
Hladyuk, Vadym ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
The purpose of this work is to create a complete picture of the retina, by stitching together a number of partial photos. Since there is no working solution which would be able to capture the entire retina in one picture, this is an important problem to cover. The results will be demonstrated at the end of the text. The problem of stitching partial pictures together was solved by extracting vessels in retinal images, finding key points in images, finding common key points, calculating a transformation matrix and transforming one image into another. After a consultation with an ophthalmologist I was able to define steps which will allow me to further improve the work, which are analyzed in texts. The thesis will provide the reader knowledge about the eye apparatus. It will also introduce field of color models, image formats, algorithms for searching for key points, the transformation of the images themselves and it will also provide a possible way to compose retinal images and also suggest possible improvements.
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Similar Photo Searching
Rosa, Štěpán ; Mlích, Jozef (referee) ; Beran, Vítězslav (advisor)
This paper describes the way to realization such an application, where a user chooses a photo database to working with and enters a photo into the system. The system using a visual vocabulary finds the most similar photos from the database and offers tags of the searched photo with a suitable form based on the tag statistical analysis of this photo.
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Photo Instead of QR Code
Štol, Jakub ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
This thesis focuses on create system, which according to user's photo search the most similar photo in dataset a display additional information about this photo such as photo content, place and author. The system is primarily focused on fields, where the user wants to use this system and get information, which he want such as museums or galleries. Theoretical part focuses on concept system according to methods of image processing and searching image in the dataset. Practical part focuses on concept creating web application, which display more information about the photo via web interface.
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Analysis of ZED stereocamera in outdoor environment
Svoboda, Ondřej ; Věchet, Stanislav (referee) ; Krejsa, Jiří (advisor)
The Master thesis is focused on analyzing stereo camera ZED in the outdoor environment. There is compared ZEDfu visual odometry with commonly used methods like GPS or wheel odometry. Moreover, the thesis includes analyses of SLAM in the changeable outdoor environment, too. The simultaneous mapping and localization in RTAB-Map were processed separately with SIFT and BRISK descriptors. The aim of this master thesis is to analyze the behaviour ZED camera in the outdoor environment for future implementation in mobile robotics.
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Video Content Summarization
Jaška, Roman ; Kolář, Martin (referee) ; Beran, Vítězslav (advisor)
The amount surveillance footage recorded each day is too large for human operators to analyze. A video summary system to process and refine this video data would prove beneficial in many instances. This work defines the problem in terms of its inputs, outputs and sub-problems, identifies suitable techniques and existing works as well as describes a design of such system. The system is implemented, and the results are examined.
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Object tracking in video
Boszorád, Matej ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with the issue of tracking multiple objects in a video, specifically focusing on non-learning algorithms. The first chapter represents the theoretical part of the thesis, in which some of the often used tracking methods are described, such as mean-shift, scale-invariant object transformation, Kalman filter, particle filter and Gabor wavelet transformation. These algorithms are broken down by properties they use for proper tracking. The chapter also contains section assignment problem, which is mainly concerned with Hungarian algorithm. The next part describes options of merging multiple tracking methods that are broken down by construction type into parallel, cascade, weighted and discriminatory with example for each one. Moreover there is described adaptability of the tracking system. Bellow are described problems which may occur during tracking and possible solutions to them. This section consists of a solution of image noise, changes in illumination, appearance and extinction of an object, focusing mainly on solving the problem of object occlusion. Within the practical part is created algorithm composed of different types of tracking, the results of which are then compared with selected tracking systems from the multiple object tracking benchmark. The practical part includes the tools used and the explanation of the design, in which the main classes and methods used for the tracking are explained. Besides that, this section describes parallel merging and tracking adaptability . The results of the thesis contain a comparison of the use of tracking techniques separately and together. To compare the results, videos for pedestrian tracking and face tracking were used. This thesis was based on the assumption that merging multiple monitoring systems will help with the improvement of the tracking, which was confirmed by the results.
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Gamification of line-follower robot videorecordings
Soboňa, Tomáš ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This bacheor’s thesis is concerned with the processing of a vehicle’s trajectory following a black line located on an unchanging white background, and subsequently comparing of the quality of each vehicle’s covered distance on this trajectory. The first part of the thesis describes the theory for recognizing the track, individual graphic tags, as well as detection of important points in the picture and their correlation with points in another picture, for which an algorithm SIFT is used. The second part deals with the description of the program, which was created as part of this work, its classes and methods. The program is written in Python, for image processing is used mainly an open source library OpenCV and, to a lesser extent, the NumPy library. Finally, the results are concluded at the end of the thesis.
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