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Face Detection in Video
Hypský, Roman ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
This bachelor's thesis describes detection of faces in video. Methods for human skin detection are described, both using the parametric approach and using the Gaussian distribution. The following is an analysis of face detection methods using the invariant features and using the machine learning methods. A particular emphasis was placed on face detection using the Viola-Jones detector using AdaBoost algorithm. The thesis also describes a practical implementation of the face detector, which was implemented in C++ using OpenCV library. Finally, the described methods are evaluated and the future project development is analyzed.
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Face recognition
Škrobák, Dalibor ; Číka, Petr (referee) ; Kyselý, František (advisor)
This thesis is focused on face detection in static picture. Theoretical part contains color spaces (RGB, HSI, YCbCr), methods for skin detection (explicit, parametric or non-parametric methods), image metric, edge detection, mathematical morphology, methods for classification faces (appearance-based methods, feature invariant approaches, knowledge-based methods, template matching methods). Practical part of this thesis contains concept and practical realization two algorithms for segmentation skin in static image (simple method based on Cr chroma components and statistical method). Practical part contains concept and practical realization two algorithms for classification face (appearance-based method and template matching method) too.
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Recognition of Objects and Gestures in Image
Johanová, Daniela ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
This thesis is focused on gesture recognition in video. The main purpose of this thesis was to create an algorithm and an application that can recognize selected gestures using a~video obtained through a~standard webcamera. The intention was to control an application program, such as video player. The approach used to achieve this goal was to exploit methods of feature extraction, tracking, and machine learning.
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Game with Hand Gesture Control
Kartous, Petr ; Zemčík, Pavel (referee) ; Hradiš, Michal (advisor)
This work is focused on controlling the game by using hand gestures. The main part of the work is image segmentation and detection of the hand in picture. For the segmentation of the image are used techniques of skin detection and the background subtraction with adaptive model of the background. Also the methods of mathematical morphology to eliminate the noise from the image and the appropriate methods for transferring images of gestures to characteristic gestures in numerical form are mentioned. In the context of the work was a simple car race game created which is controlled by hand gestures. At the end there was a testing carried out to identify the advantages and disadvantages of used methods of image segmentation and to detect the used hand gestures. There were also several sets of gestures tested by which the game is controlled. The two sets which came out of the test most successfully are applicable depending on the quality of the hand gesture recognition.
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Face Recognition
Pléha, David ; Honec, Jozef (referee) ; Horák, Karel (advisor)
Face detection in the complex image is the part of the key steps in creation of the face recognition software. In this work an algorithm, by which means it is possible to detect parts of human skin in the image with a complex background as well as the methods of the detected image filtration, is described and specified. The algorithm appears from the value of the human skin colour model, which is the main basis for the process of identification. In this work also the issue regarding the face part determination within the detected image by various hypotheses on human face is examined.
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Hand Gesture - Controlled VJ Mixer
Vlk, Jakub ; Žák, Pavel (referee) ; Polok, Lukáš (advisor)
This paper describes an implementation of a VJ Mixer controlled by hand gestures. For construction of VJ mixer is first necessary to detect hands in the picture. Therefore this paper first describes the methods of detection of human skin in an image, with an emphasis on the method of Gaussian probability distribution, which is used in the actual implementation of a program. Then some methods of detecting objects in images are described , mainly for hands and gestures. Great emphasis is placed on the method of convex defects, which was used in the final program. Finally, the procedures linking the hand gesture recognition with the video processing algorithms are described.
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Face detection in image
Pospíšil, Lukáš ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
The main puprose of this paper is to introduce some of algorithms used in face detection in images. This paper focuses on face detection by using a skin-color based segmentation that is computed in three color spectrums (RGB,YCbCr and HSV). This paper also includes software for face detection in pictures and videos.
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Face Detection in Video
Hypský, Roman ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
This bachelor's thesis describes detection of faces in video. Methods for human skin detection are described, both using the parametric approach and using the Gaussian distribution. The following is an analysis of face detection methods using the invariant features and using the machine learning methods. A particular emphasis was placed on face detection using the Viola-Jones detector using AdaBoost algorithm. The thesis also describes a practical implementation of the face detector, which was implemented in C++ using OpenCV library. Finally, the described methods are evaluated and the future project development is analyzed.
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Hand Gesture - Controlled VJ Mixer
Vlk, Jakub ; Žák, Pavel (referee) ; Polok, Lukáš (advisor)
This paper describes an implementation of a VJ Mixer controlled by hand gestures. For construction of VJ mixer is first necessary to detect hands in the picture. Therefore this paper first describes the methods of detection of human skin in an image, with an emphasis on the method of Gaussian probability distribution, which is used in the actual implementation of a program. Then some methods of detecting objects in images are described , mainly for hands and gestures. Great emphasis is placed on the method of convex defects, which was used in the final program. Finally, the procedures linking the hand gesture recognition with the video processing algorithms are described.
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