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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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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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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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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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