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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 recognitions in images
Krhut, Miloš ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The master thesis deals with the topic of detecting faces in digital images. There are generally described and classified the most frequently used methods and discussed their advantages and disadvantages. More detailed is described skin color detection, eye and mouth detection and are teoretically described machine learning algorithms and detection based on Haar-classifiers. The work aims to implementation of these methods in the OpenCV library, it refers to practical application of them a finally compares different provided trained files.
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Face Detection and Recognition
Ponzer, Martin ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper discusses problems of computer vision, which deals with face detection and recognition in image and video sequence at real time. All methods are designed for color images and are based on skin detection on the basis of information of human skin color. For skin detection is used very effective method Gaussian distribution. All of the areas, which have human skin color, are classified. This classification specifies, which area is or isn’t face. For face detection is used correlation method, complete with eigenfaces method. All areas classified as a face are subsequently recognized by the eigenfaces method. Result of recognition phase is information about human identity.
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Face Detection in Video
Kolman, Aleš ; Řezníček, Ivo (referee) ; Polok, Lukáš (advisor)
The project is focused on face detection in video. Firstly, it contains a summary of basic color models. Secondly, you can find the description and comparison of the basic methods for detection of human skin with a practical example of implementation of parametric detector. Thirdly, a theoretical basis for face detection and face tracking in a video containing a list of basic concepts and methods of this issue follows. Greater emphasis is placed on the description of machine learning algorithm AdaBoost and description of the possible application of the Kalman filter for the purpose of face tracking. Design, implementation and testing of library accomplished within the master thesis are listed in the final part of this thesis.
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Gestural Interface for Computer Control
Burdík, Vojtěch ; Beneš, Radek (referee) ; Přinosil, Jiří (advisor)
This work focuses on the relatively new computer branch – a computer vision. Work is concentrated on object recognition, localization and reaction to specific movements. The aim is to build a program that will be able to use hand movements to control computer, to the gesture as defined by the fingers and palms respond and make it the event. The objective should be achieved without the use of special sensors or more cameras, but only with one common webcam. For the image processing function from OpenCV library were used and program was built. Evaluation of function is based on functional verification in practice, evaluation of speed, accuracy and quality of object recognition. Following the scheme, how could program for gestural controlling the computer should look, was created, and then his realization in a simple program was made. This program is able to recognize the object in an image, in this case a hand, and through an evaluation of its movements control cursor on a computer with a possibility of simulation pressing the left mouse button. Program continuously allows the documents to scroll horizontal and vertical direction. The program is very robust and work with him is very simple.
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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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