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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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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 in Video on GPU
Tesař, Martin ; Nečas, Ondřej (referee) ; Polok, Lukáš (advisor)
This work deals with task of face detection on graphic card. First part is the introduction to face detection methods focusing on detector proposed by Viola and Jones. Further, this work studies the possibilities of mapping detector's key parts on graphic card. Next part describes implementation details of designed application. The end of work include results and comparison with CPU approach. The last chapter summarizes the whole work and proposes future possibilities of development.
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Design and Implementation of a Family Photo Management Web Application
Macháč, Jan ; Kindlová, Dita (referee) ; Dydowicz, Petr (advisor)
This thesis focuses on the design and development of a web application that offers help in managing family photographic material, with the emphasis on data integrity and security, and maximum transparency when handling personal information. The application will be usable on any device with a screen, web browser and internet connection. One of its key features will be face detection on uploaded photographs.
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