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Recognizing Faces within Image
Svoboda, Pavel ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
The essence of face recognition within the image is generally computer vision, which provides methods and algorithms for the implementation. Some of them are described just in this work. Whole process is split in to three main phases. These are detection, aligning of detected faces and finally its recognition. Algorithms which are used to applied in given issue and which are still in progress from todays view are mentioned in every phase. Implementation is build up on three main algorithms, AdaBoost to obtain the classifier for detection, method of aligning face by principal features and method of Eigenfaces for recognizing. There are theoretically described except already mentioned algorithms neural networks for detection, ASM - Active Shape Models algorithm for aligning and AAM - Active Appearance Model for recognition. In the end there are tables of data retrieved by implemented system, which evaluated the main implementation.
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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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Person Identification
Ťapuška, Tomáš ; Zuzaňák, Jiří (referee) ; Hradiš, Michal (advisor)
This master's thesis is about the most known methods for face recognition. There are described their advantages and disadvantages. This work is specialized at holistic methods for face recognition, which are working with 2D pictures of people. I implemented the automatic system for face recognition according to digital picture of face. There was, in this system, implemented these methods: KNN (K nearest neighbour), PCA (Principal component analysis) and LDP (Linear doscriminant projection). There was done some tests to compare implemented methods. The tests was done on the pictures from dataset FERET. In the conclusion of this text are considered implemented approaches and is marked the best method for face recognition from implemented.
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Face Recognition
Kopřiva, Adam ; Hradiš, Michal (referee) ; Chmelař, Petr (advisor)
This master's thesis considers methods of face recognition. There are described methods with different approachs: knowledge-based methods, feature invariant approaches, template matching methods and appearance-based methods. This master's thesis is focused particulary on template matching method and statistical methods like a principal component analysis (PCA) and linear discriminant analysis (LDA). There are described in detail template matching methods like active shape models (ASM) and active appearance models (AAM).
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Fabrication and Characterization of Templates for Fabrication of Nanowires
Lednický, Tomáš ; Čechal, Jan (referee) ; Škoda, David (advisor)
The bachelor thesis is focused on fabrication of alumina templates by anodization of pure aluminium. The theoretical part discusses the growing process of anodized oxide layers and its dependency on the crucial parameters (solutions, anodization voltage, time). The theoretical part is particularly based on literature retrieval. The experimental part is aimed to the fabrication of alumina membranes: the apparatus design, aluminium foils preparation, aluminium anodization, membrane modifications for next applications (nanowires deposition) and membrane characterization.
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Face Identification on Android Platform
Karhánek, Martin ; Řezníček, Ivo (referee) ; Láník, Aleš (advisor)
This work describes ways to use a person identification based on faces on mobile devices with Android platform. A reader is introduced into a structure of this system and a way to create applications for it. Besides, there are also methods usable to the face identification. Some of these methods (used in an implementation) are described in more detail. This work also contains a description of model AAM (Active Appearance Model) for implementing in mobile devices and evaluation of used algorithms results.
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Face Recognition
Kopřiva, Adam ; Hradiš, Michal (referee) ; Chmelař, Petr (advisor)
This master's thesis considers methods of face recognition. There are described methods with different approachs: knowledge-based methods, feature invariant approaches, template matching methods and appearance-based methods. This master's thesis is focused particulary on template matching method and statistical methods like a principal component analysis (PCA) and linear discriminant analysis (LDA). There are described in detail template matching methods like active shape models (ASM) and active appearance models (AAM).
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Person Identification
Ťapuška, Tomáš ; Zuzaňák, Jiří (referee) ; Hradiš, Michal (advisor)
This master's thesis is about the most known methods for face recognition. There are described their advantages and disadvantages. This work is specialized at holistic methods for face recognition, which are working with 2D pictures of people. I implemented the automatic system for face recognition according to digital picture of face. There was, in this system, implemented these methods: KNN (K nearest neighbour), PCA (Principal component analysis) and LDP (Linear doscriminant projection). There was done some tests to compare implemented methods. The tests was done on the pictures from dataset FERET. In the conclusion of this text are considered implemented approaches and is marked the best method for face recognition from implemented.
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|
|
Face Identification on Android Platform
Karhánek, Martin ; Řezníček, Ivo (referee) ; Láník, Aleš (advisor)
This work describes ways to use a person identification based on faces on mobile devices with Android platform. A reader is introduced into a structure of this system and a way to create applications for it. Besides, there are also methods usable to the face identification. Some of these methods (used in an implementation) are described in more detail. This work also contains a description of model AAM (Active Appearance Model) for implementing in mobile devices and evaluation of used algorithms results.
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|
|
Recognizing Faces within Image
Svoboda, Pavel ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
The essence of face recognition within the image is generally computer vision, which provides methods and algorithms for the implementation. Some of them are described just in this work. Whole process is split in to three main phases. These are detection, aligning of detected faces and finally its recognition. Algorithms which are used to applied in given issue and which are still in progress from todays view are mentioned in every phase. Implementation is build up on three main algorithms, AdaBoost to obtain the classifier for detection, method of aligning face by principal features and method of Eigenfaces for recognizing. There are theoretically described except already mentioned algorithms neural networks for detection, ASM - Active Shape Models algorithm for aligning and AAM - Active Appearance Model for recognition. In the end there are tables of data retrieved by implemented system, which evaluated the main implementation.
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