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People tracking in sparse crowd using multiple cameras
Zimmermann, Jan ; Hlaváč, Václav (advisor) ; Suk, Tomáš (referee)
In this thesis, we introduce a new algorithm for tracking of multiple people in image sequences from surveillance cameras. The algorithm handle with trustworthiness in similarity measure of human gures in images. All decisions are made as trustworthily as possible. The algorithm nds out the number of people in the scene autonomously. It deals with potential temporary occlusions of people in image. The tracking algorithm does not suffer from the problem of human model initialization as some other methods do. The implementation of our algorithm is a part of this thesis. This implementation has veri ed the characteristics of the algorithm. We have used two different methods for the image segmentation. Both method prove successful in different conditions. We have used a color information to compare the visual similarity. Suitable future extensions are suggested at the end of this thesis.
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Comparing RNA structures
Zimmermann, Jan ; Mráz, František (advisor) ; Hoffmann, Petr (referee)
RNA sequences creates complicated secondary structures, unlike DNA. In the presented work we state techniques for automatic similarity searching among RNA sequences. The similarity of RNA sequences we understand not only based on primary structure, but based on secondary structure as well. The goal of this work is to create techniques for cutting of various sequences, which are read from di®erent sources. We define terms as structural alignment, structural profile and structural consensus, which are a generalization of terms as sequence alignment, sequence profile and sequence consensus. Part of this work is an application RNAcut. It is able to cut RNA sequences based on its primary and secondary structure. In the application we implement most of algorithms, which are described in this work.
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Comparing RNA structures
Zimmermann, Jan ; Hoffmann, Petr (referee) ; Mráz, František (advisor)
RNA sequences creates complicated secondary structures, unlike DNA. In the presented work we state techniques for automatic similarity searching among RNA sequences. The similarity of RNA sequences we understand not only based on primary structure, but based on secondary structure as well. The goal of this work is to create techniques for cutting of various sequences, which are read from di®erent sources. We define terms as structural alignment, structural profile and structural consensus, which are a generalization of terms as sequence alignment, sequence profile and sequence consensus. Part of this work is an application RNAcut. It is able to cut RNA sequences based on its primary and secondary structure. In the application we implement most of algorithms, which are described in this work.
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|
|
People tracking in sparse crowd using multiple cameras
Zimmermann, Jan ; Suk, Tomáš (referee) ; Hlaváč, Václav (advisor)
In this thesis, we introduce a new algorithm for tracking of multiple people in image sequences from surveillance cameras. The algorithm handle with trustworthiness in similarity measure of human gures in images. All decisions are made as trustworthily as possible. The algorithm nds out the number of people in the scene autonomously. It deals with potential temporary occlusions of people in image. The tracking algorithm does not suffer from the problem of human model initialization as some other methods do. The implementation of our algorithm is a part of this thesis. This implementation has veri ed the characteristics of the algorithm. We have used two different methods for the image segmentation. Both method prove successful in different conditions. We have used a color information to compare the visual similarity. Suitable future extensions are suggested at the end of this thesis.
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