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Evaluation of Methods of Stereo Image Processing
Juráček, Ivo ; Španěl, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis addresses the correlation between two pictures and its application to a real example using a camera which is a part of a stereo camera. It suggests how to use correlation to find specific patterns in pictures whereas it is possible to calculate the movement between two scaled pictures which is done by resampling. The accuracy of correlation is then shown when pictures are compensated using affine transformation in order to verify the accuracy of correlation. To further increase the correlation accuracy, it is possible to use a corner detector, it finds main points in a shot and then it searches for a match in another shot using correlation. Final results using this method are also mentioned in this thesis.
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Harris corner detector
Květný, Michal ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
This bachelor’s thesis deals with application of Harris corner detector for finding corner points in images and models. This thesis also contains an implementation of the algorithms in Python programming language. Programs are tested on real images captured by camera and models created by 3D scanning.
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Shot Boundary Detection
Klicnar, Lukáš ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Shot boundary detection is a process of automatically finding the boundaries between shots in a video. This work primarily deals with detection of hard-cuts, but gradual transitions are also considered. At first, fundamental terms of this field are explained, commonly used methods are shortly described. The main part of this work is design and implementation of system for shot boundary detection based on combination of two methods. The first one is comparison of color histograms for adjacent frames. Second approach is based on visual feature tracking. The analysis of behavior of those features is done by estimating their first derivatives. Proposed system was tested on small, manually annotated set of test data, which showed that both features are suitable for this task. Detector proved its ability to find hard-cuts with good precision. It was also able to detect some gradual transitions.
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Harris corner detector
Květný, Michal ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
This bachelor’s thesis deals with application of Harris corner detector for finding corner points in images and models. This thesis also contains an implementation of the algorithms in Python programming language. Programs are tested on real images captured by camera and models created by 3D scanning.
|
|
|
Evaluation of Methods of Stereo Image Processing
Juráček, Ivo ; Španěl, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis addresses the correlation between two pictures and its application to a real example using a camera which is a part of a stereo camera. It suggests how to use correlation to find specific patterns in pictures whereas it is possible to calculate the movement between two scaled pictures which is done by resampling. The accuracy of correlation is then shown when pictures are compensated using affine transformation in order to verify the accuracy of correlation. To further increase the correlation accuracy, it is possible to use a corner detector, it finds main points in a shot and then it searches for a match in another shot using correlation. Final results using this method are also mentioned in this thesis.
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|
|
Shot Boundary Detection
Klicnar, Lukáš ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Shot boundary detection is a process of automatically finding the boundaries between shots in a video. This work primarily deals with detection of hard-cuts, but gradual transitions are also considered. At first, fundamental terms of this field are explained, commonly used methods are shortly described. The main part of this work is design and implementation of system for shot boundary detection based on combination of two methods. The first one is comparison of color histograms for adjacent frames. Second approach is based on visual feature tracking. The analysis of behavior of those features is done by estimating their first derivatives. Proposed system was tested on small, manually annotated set of test data, which showed that both features are suitable for this task. Detector proved its ability to find hard-cuts with good precision. It was also able to detect some gradual transitions.
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