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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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Automatic Content-Based Image Categorization
Němec, Ladislav ; Španěl, Michal (referee) ; Veľas, Martin (advisor)
This thesis deals with automatic content-based image classification. The main goal of this work is implementation of application which is able to perform this task automatically. The solution consists of variable system using local image features extraction and visual vocabulary built by k-means method. Bag Of Words representation is used as a global feature describing each image. Support Vector Machines - the final component of this system - perform the classification based on this representation. In the last chapter, the results of this experimental system are presented.
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Optic flow software module design
Grulich, Jan ; Růžička, Michal (referee) ; Věchet, Stanislav (advisor)
This bachelor thesis is focused on the analysis of optical flow. The first part is dedicated to the theoretical analysis of the motion of image features. Especially important is finding quality features that can be tracked in a videosequence. Detailed mathematical description of the necessary algorithms is presented. The second part describes the software and its functions with the implemented algorithms. The main function is determining the distance of an object from the camera based on its velocity. Empirical tests of this function are presented.
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Detection of Corresponding Points in Images
Komosný, Petr ; Hradiš, Michal (referee) ; Španěl, Michal (advisor)
This thesis is interested in detection of corresponding points in images, which display the same object, eventually some of important elements and synchronizing these images. The aim of this thesis is to find, study and choose suitable algorithm for detecting interesting points in image. This algorithm will be apply at couple of images and in these images will find couples of corresponding points across these images. Functional output of this thesis will be application which will realize choosen interesting points detector, algorithm for finding correspondencies of regions and their synchronizing and joint them to one output image.
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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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Interest-Point Detection on CUDA
Ryba, Jan ; Řezníček, Ivo (referee) ; Herout, Adam (advisor)
Corner point detection is one of many functions used in computer vision for tasks such as tracking, detecting objects, comparing images and much more. Many of the algorithms are complex and require a lot of CPU time. This is where the CUDA platform comes in. CUDA kernels run parallely on graphic accelerators can rapidly decrease time needed for execution, allowing even these complex calculations to work in real time or even better. Text focuces on Moravec and Harris corner detection algorithms and their effective implementation on CUDA. Examination of potetntial and performance of CUDA platform is also importatnt.
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Eye Tracking in User Interfaces
Jurzykowski, Michal ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
Tato diplomová práce byla vytvořena během studijního pobytu na Uviversity of Estern Finland, Joensuu, Finsko. Tato diplomová práce se zabývá využitím technologie sledování pohledu neboli také sledování pohybu očí (Eye-Tracking) pro interakci člověk-počítač (Human-Computer Interaction (HCI)). Navržený a realizovaný systém mapuje pozici bodu pohledu/zájmu (the point of gaze), která odpovídá souřadnicím v souřadnicovém systému kamery scény do souřadnicového systému displeje. Zároveň tento systém kompenzuje pohyby uživatele a tím odstraňuje jeden z hlavních problémů využití sledování pohledu v HCI. Toho je dosaženo díky stanovení transformace mezi projektivním prostorem scény a projektivním prostorem displeje. Za použití význačných bodů (interesting points), které jsou nalezeny a popsány pomocí metody SURF, vyhledání a spárování korespondujících bodů a vypočítání homografie. Systém byl testován s využitím testovacích bodů, které byly rozložené po celé ploše displeje.
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Magic Projection
Kaisler, Vojtěch ; Polok, Lukáš (referee) ; Zachariáš, Michal (advisor)
The bachelor thesis describes the design and implementation of an application which projects an image on a mobile canvas. The user then moves the canvas within the projection space. The projection is always focused only on this canvas. The thesis deals with tracking of movement, rotation and tilt of the screen. A camera with an infrared filter is used for tracking the canvas fitted with infrared LEDs. The thesis mentions two different types of projection.
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Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
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Determination of Motion Parameters in Machine Vision
Dušek, Stanislav ; Horák, Karel (referee) ; Janáková, Ilona (advisor)
This thesis describe about determination of camera motion parameters in plane. At first there are introduce the basics of motion tracking, is focused to find out displacement between two input images. Below is describe the algorithm GoodFeatruresToTrack, which find out the most significant point in a first image. The point is search out the good point, which will be easy to track in next image, reduce the data volume and prepare the input information (array of significant point) for the algorithm Lucas-Kanade optical flow. In second part is deal with processing and utilization estimations optical flow. There is median filtration, below is describe computation of homogenous transformation, which describe all affine transformation in affine space. As the result are coordinates, which describe the shift between the two input images as X-axis and Y-axis value. The project used the library Open Computer Vision.
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