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Computer Interface Based on User's Head Position
Chmiel, Filip ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
This paper presents the method for a head pose and orientation detection based on computer vision techniques. The method is based on the AdaBoost approach for initial face recognition and the optical flow technique for further object tracking. The detection results are further interpreted and stabilized. The method is designed for usage in designing and building the innovative user interfaces.
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Detection of face parts in the thermographic spectrum
Šujan, Miroslav ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
Master´s thesis deals with current problems of face detection and its parts in the infrared thermographic spectrum. Most previously published literature deals with the detection in the visible spectrum, making the thermographic detection range an interesting alternative. The work deals with the processing of image signals, images and faces in thermographic spectrum, selected methods of face detection and its parts and also deals with practical system design for detecting facial parts in this spectrum and its subsequent testing.
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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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Face Detection
Šašinka, Ondřej ; Hradiš, Michal (referee) ; Juránek, Roman (advisor)
This MSc Thesis deals with face detection in image. In this approach, facial features (eyes, nose, mouth corners) are detected first and then joined to the whole face. For the facial features detection, classifiers trained with AdaBoost algorithm are used. Haar wavelets are used as features for classification.
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Face detection in image
Koudela, Ondřej ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
This work is basic overview over methods of face detection in picture and it's components. The main part of the work is an example of algorithm developed in MATLAB programming language for face detection based on skin color segmentation in different color spaces and their implementation in real time. The basic algorithm is discussed in several steps with shown results for each of color spaces and in the end of the work is evaluation of used methods. This work also includes a simulation of processing real-time detection in MATLAB Simulink.
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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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Video-Based Human-Computer Interface
Caha, Miloš ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
A bachelor thesis deals with methods about a detection of direction of look and with theirs following applications for PCs control. The thesis summarises and describes the most widely used methods for individual phases of the mentioned detection. Especially, use of a face detector and of convolution filters for searching of significant points in the face is used. The work is concentrated on a design and a description of an implementation of the application which demonstrates the method of contactless PCs control.
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Gaze Detection
Caha, Miloš ; Herout, Adam (referee) ; Španěl, Michal (advisor)
Main object of this work is to design and implement the algorithm for look direction determination, respectively the head movement. More specifically, it is a system that searches face in the video and then detects points, suitable for view direction estimation of tracked person. Estimation is realized using searching transformation, which has been performed on key points during head movement. For accuracy enhancement the calibration frames are used. Calibration frames determines the key points transformation in defined view directions. Main result is an application able to determine deflection of head from straight position in horizontal and vertical direction for tracked person. Output doesn't contain only information about deflection direction, but it also contains the size of deflection.
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Camera based eye tracking
Otáhal, Miroslav ; Walek, Petr (referee) ; Janoušek, Oto (advisor)
The aim of this master thesis is to understand problematic of eyes movement tracking using webcam. In individual chapters there are introduced basic approaches of eyes movement tracking, based on this method we can get the position of eye pupil and identify where a person looks. The part of this work is program in Matlab, which using the method of infrared detection follow the position of eye pupil and transfer this movements to the movements on the computer screen. Using this program it was tested several volunteers and the results of detection were transferred to the visual form. As part of this program it was created template for assessment of accuracy of used method. At the end of work are discussed achieved results.
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