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Controlling Computer Using Gestures
Lacko, Peter ; Herout, Adam (referee) ; Juránek, Roman (advisor)
This work deals with creation of system for controlling computer through webcam with gestures. Gesture in this work can be viewed as hand motion forming some pattern. In the beginning are described methods for hand detection, hand tracking and pattern recognition. Afterwards comes description of system and it's implementation with tests evaluation. Outcome of this work is program for simple control of document viewer and multimedia player.
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Detecting Objects in Images
Kubínek, Jiří ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This work is dedicated to methods used for object detection in images. There is a summary of several approaches and algorithms to solve this matter, especially AdaBoost algorithm with its improvement, WaldBoost and several features used for object detection. Vital part of this work is dedicated to extending training datasets for classifier training and extending the current object detection framework with histogram of gradients features implementation. Integral part of this work is analysis of results by experiments evaluation.
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Face detection in image
Malach, Tobiáš ; Přinosil, Jiří (referee) ; Mézl, Martin (advisor)
This paper presents an overview of face detection methods. Keywords and basic principles of classification of images and it’s parts are explained. Significant part of this paper is occupied with presentation of Viola-Jones detector and it’s implementation in Matlab. Detector Viola-Jones ranks among the most used methods for face detection in practice, which was the reason for detailed analysis and subsequent implementation. Detector is theoretically described, basic steps of algorithm and training algorithm are discussed. Based on theoretical analysis, detector is implemented in Matlab. Properties of implemented detector are objectively evaluated and compared with of two different implementations.
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Processing of Video Records
Čerešňák, Michal ; Drahanský, Martin (referee) ; Zemčík, Pavel (advisor)
V této práci je prezentován systém pro zpracování videa se zaměřením na detekci a rozeznávání obličejů. Systém zpracovává video stream z kamery v reálném čase. K detekci obličejů využívá ViolaJones detektor. Pro rozeznávání obličejů je použita metoda SURF. Systém je implementován v jazyce C# a využívá knihovnu OpenCV a Emgu CV wrapper.
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Automatic face and facial feature detection
Krolikowski, Martin ; Kohoutek, Michal (referee) ; Přinosil, Jiří (advisor)
The master thesis presents an overview of face detection task in color, static images. Face detection term is posed in the context of various branches. Main concepts of face detection and also their relationships are described. Individual approaches are divided into groups and then define in turn. In the thesis is in detail described algorithm AdaBoost, which is selected on the basis of its properties. Especially speed of computation and good detection results are key features. In the scope of this work Viola-Jones detector was implemented. This detector was trained with face pictures from public accessible database. Combination of Viola-Jones detector with simple color detector is described. In the thesis is also presented experiment approach to facial features detection.
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Face detection in image
Malach, Tobiáš ; Přinosil, Jiří (referee) ; Mézl, Martin (advisor)
This paper presents an overview of face detection methods. Keywords and basic principles of classification of images and it’s parts are explained. Significant part of this paper is occupied with presentation of Viola-Jones detector and it’s implementation in Matlab. Detector Viola-Jones ranks among the most used methods for face detection in practice, which was the reason for detailed analysis and subsequent implementation. Detector is theoretically described, basic steps of algorithm and training algorithm are discussed. Based on theoretical analysis, detector is implemented in Matlab. Properties of implemented detector are objectively evaluated and compared with of two different implementations.
|
|
|
Controlling Computer Using Gestures
Lacko, Peter ; Herout, Adam (referee) ; Juránek, Roman (advisor)
This work deals with creation of system for controlling computer through webcam with gestures. Gesture in this work can be viewed as hand motion forming some pattern. In the beginning are described methods for hand detection, hand tracking and pattern recognition. Afterwards comes description of system and it's implementation with tests evaluation. Outcome of this work is program for simple control of document viewer and multimedia player.
|
|
|
Processing of Video Records
Čerešňák, Michal ; Drahanský, Martin (referee) ; Zemčík, Pavel (advisor)
V této práci je prezentován systém pro zpracování videa se zaměřením na detekci a rozeznávání obličejů. Systém zpracovává video stream z kamery v reálném čase. K detekci obličejů využívá ViolaJones detektor. Pro rozeznávání obličejů je použita metoda SURF. Systém je implementován v jazyce C# a využívá knihovnu OpenCV a Emgu CV wrapper.
|
|
|
Detecting Objects in Images
Kubínek, Jiří ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
This work is dedicated to methods used for object detection in images. There is a summary of several approaches and algorithms to solve this matter, especially AdaBoost algorithm with its improvement, WaldBoost and several features used for object detection. Vital part of this work is dedicated to extending training datasets for classifier training and extending the current object detection framework with histogram of gradients features implementation. Integral part of this work is analysis of results by experiments evaluation.
|
|
|
Automatic face and facial feature detection
Krolikowski, Martin ; Kohoutek, Michal (referee) ; Přinosil, Jiří (advisor)
The master thesis presents an overview of face detection task in color, static images. Face detection term is posed in the context of various branches. Main concepts of face detection and also their relationships are described. Individual approaches are divided into groups and then define in turn. In the thesis is in detail described algorithm AdaBoost, which is selected on the basis of its properties. Especially speed of computation and good detection results are key features. In the scope of this work Viola-Jones detector was implemented. This detector was trained with face pictures from public accessible database. Combination of Viola-Jones detector with simple color detector is described. In the thesis is also presented experiment approach to facial features detection.
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