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Monitoring of human body in videosequence
Plačko, Michal ; Šmirg, Ondřej (referee) ; Číka, Petr (advisor)
This thesis deals with human body detection and gestures tracking in videosequences. First, processing of videosequences in general is described. Further, different methods of human body detection are described and represented by significant papers. The most of the attention is focused on detection by real AdaBoost algorithm based on Haar-like features and Edgelet features. The practical part starts with selection of method that is implemented in this thesis. This method is detection by real AdaBoost based on Haar-like features. Further, different options of videosequence processing in JAVA are researched with justification of choice OpenCV library with JavaCV wrapper, which is used in this thesis. In the end, application itself is described, including description of GUI and description of each class and its functionality.
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Pattern Recognition Using AdaBoost
Wrhel, Vladimír ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
This paper deals about AdaBoost algorithm, which is used to create a strong classification function using a number of weak classifiers. We familiarize ourselves with modifications of AdaBoost, namely Real AdaBoost, WaldBoost, FloatBoost and TCAcu. These modifications improve some of the properties of algorithm AdaBoost. We discuss some properties of feature and weak classifiers. We show a class of tasks for which AdaBoost algorithm is applicable. We indicate implementation of the library containing that method and we present some tests performed on the implemented library.
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Pattern Recognition Using AdaBoost
Wrhel, Vladimír ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
This paper deals about AdaBoost algorithm, which is used to create a strong classification function using a number of weak classifiers. We familiarize ourselves with modifications of AdaBoost, namely Real AdaBoost, WaldBoost, FloatBoost and TCAcu. These modifications improve some of the properties of algorithm AdaBoost. We discuss some properties of feature and weak classifiers. We show a class of tasks for which AdaBoost algorithm is applicable. We indicate implementation of the library containing that method and we present some tests performed on the implemented library.
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Monitoring of human body in videosequence
Plačko, Michal ; Šmirg, Ondřej (referee) ; Číka, Petr (advisor)
This thesis deals with human body detection and gestures tracking in videosequences. First, processing of videosequences in general is described. Further, different methods of human body detection are described and represented by significant papers. The most of the attention is focused on detection by real AdaBoost algorithm based on Haar-like features and Edgelet features. The practical part starts with selection of method that is implemented in this thesis. This method is detection by real AdaBoost based on Haar-like features. Further, different options of videosequence processing in JAVA are researched with justification of choice OpenCV library with JavaCV wrapper, which is used in this thesis. In the end, application itself is described, including description of GUI and description of each class and its functionality.
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