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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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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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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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PC control via eyes
Neuwirth, Tomáš ; Číp, Pavel (referee) ; Horák, Karel (advisor)
The presented master thesis deals with the evaluation of the position of the iris compared with surroundings of the eye. This technique is supposed to be use for computer control. The created software works in real-time mode, the pictures are taken with an ordinary webcam. The first part of the work presents basic algorithms used in computer vision for edit of images. The following part is focused on abilities of methods to find the face, eyes and to detect the iris. The detection and the subsequent separation of the face is based on the recognition of skin colour in the YCbCr color space. The position of eye is then searched in the face by Haar-like features. The darkest part of the eye is found by horizontal projection from surroundings and the seed point is started from this place. From the area which is filled by the seed method (Flood Fill) and which shows the iris, the cursor movement is controlled by obtained x and y position.
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Head Pose Estimation and Tracking
Pospíšil, Aleš ; Krajsa, Ondřej (referee) ; Přinosil, Jiří (advisor)
Diplomová práce je zaměřena na problematiku detekce a sledování polohy hlavy v obraze jako jednu s možností jak zlepšit možnosti interakce mezi počítačem a člověkem. Hlavním přínosem diplomové práce je využití inovativních hardwarových a softwarových technologií jakými jsou Microsoft Kinect, Point Cloud Library a CImg Library. Na úvod je představeno shrnutí předchozích prací na podobné téma. Následuje charakteristika a popis databáze, která byla vytvořena pro účely diplomové práce. Vyvinutý systém pro detekci a sledování polohy hlavy je založený na akvizici 3D obrazových dat a registračním algoritmu Iterative Closest Point. V závěru diplomové práce je nabídnuto hodnocení vzniklého systému a jsou navrženy možnosti jeho budoucího zlepšení.
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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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Real time face recognizer
Juráček, Aleš ; Přinosil, Jiří (referee) ; Richter, Miloslav (advisor)
My diploma thesis deals about face detection in picture. I try to outline problems of computer vision, artificial intelligence and machine learning. I described in details the proposed detection by Viola and Jones, which uses AdaBoost learning algorithm. This method was deliberately chosen for speed and detection accuracy. This detector was made in programming language C / C + + using the OpenCV library. To a final learning was used database of faces images „MIT CVCL Face Database“. The main goal was to propose the face detector utilizable also in video-sequences.
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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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