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Real-time Facial Feature Tracking
Peloušek, Jan ; Mekyska, Jiří (referee) ; Přinosil, Jiří (advisor)
This thesis considers the problematic of the object recognition in a digital picture, particularly about the human face recognition and its components. There are described the basics of the computer vision, the object detector Viola-Jones, its computer realization with help of the OpenCV libraries and the test results. This thesis also describes the accurate system of the facial features detection per the algorithm of the Active Shape Models and also related mechanism of the classifier training, including the software implementation.
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Windows Phone 7 Application for Traffic Sign Recognition
Dvořák, Marek ; Orság, Filip (referee) ; Procházka, Boris (advisor)
Purpose of this thesis is to create an application that detects and recognizes traffic signs for mobile phones running Windows Phone 7 operating system. Theoretical part contains information about history and characteristics of Windows Phone 7 system, traffic signs in Czech Republic and various methods of image processing. Practical part of this thesis describes particular implementation of recognizing of traffic signs in photographs taken with mobile phone built-in camera. In last part this app is tested in real-life conditions and results of these tests are evaluated.
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Multicameras Biometric Gateway to Identify People
Kosík, Dominik ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This thesis is about creating biometric gate to identify people. The Identification is achieved with 5 RGB cameras and one thermal camera. Thermal camera is used for detection of person. Then, from images acquired from RGB cameras, is created 3D model of photographed person. This model is then used for the identification. However due to inaccuracies in created model, identification isn't precise enough. Because of that, it's necessary to modify used algorithms processing 3D model, so better precision is achieved.
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Speed of learning multilayer network
Maceček, Aleš ; Zámečník, Dušan (referee) ; Jirsík, Václav (advisor)
Theoretical study about neural networks, especially their types of topologies and networks learning. Special attention is attended to multilayer neural network with learning backpropagation. Introduced learning algorithm backpropagation of simple networks in conjunction with descriptions of parameters affecting network learning also methods to exaluation quality of network learning. Definition moment invariants to rotation, translation and scaling. Optimalization parameters of neural networks to find the network which has the fastest learning and also the networks with the best value of recognition patterns of letters from testing set.
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Handwriting Recognition
Zouhar, David ; Řezníček, Ivo (referee) ; Mlích, Jozef (advisor)
This diploma thesis deals with handwriting recognition in real-time. It describes the ways how the intput data are processed. It is also focused on the classi cation methods, which are used for the recognition. It especially describes hidden Markov models. It also present the evaluation of the success of the recognition based on implemented experiments. The alternative keyboard for MeeGo system was created for this thesis as well. The established system achieved the success above 96%.
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Multilingual analysis of human emotional states
Rendek, Tomáš ; Koula, Ivan (referee) ; Atassi, Hicham (advisor)
This work deals with the properties of the speech signal. At the beginning it introduces a process of generation of the speech. Then, it covers the prosodic features of the speech, which represent a related characteristic of emotions. It defines an emotion itself, as well as the basic features and parameters of the human speech. For the analysis we use the program called Praat. As it is an unknown program, we devote a part of the work to it, which acquaints us with its advantages. The next part of this paper comprises also two enclosed databases containing records of particular emotional states of human. These databases were created and collected for Slovak and German language. However, none of them contain spontaneous material. Next, the work concerns a concept of the neural networks. It regards it as a possible realization of recognizing of emotional characteristics. The initial analysis presents large number of gained features, out of which only the best twelve were selected on the basis of geometric separability. These features are distinct for both sexes, as well as for both nationalities. Consequently, they are used for training with a neural network. The work concludes by summarizing of the results discussing the successfulness with recognition of emotional states. It also gives possible reasons which lead to degradation of their successful classifying. The thesis contains a CD with all the partial and ultimate results, and files with records for Slovak and German language.
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Agreements and Disagreements between Automatic and Human Speaker Recognition
Valenta, Jakub ; Matějka, Pavel (referee) ; Rohdin, Johan Andréas (advisor)
Tato práce se zabývá problémem rozpoznáváním mluvčího. Uvedený pojem je definován a doplněn o jednotlivé metody, které s ním souvisí. Cílem práce je poukázat na shody a rozdíly mezi lidským a automatickým procesem rozpoznávání mluvčího. V úvodu práce jsou popsány teoretické poznatky z obou zmíněných oblastí, tj. na jaké aspekty lidské řeči se zaměřuje člověk, resp. automatický systém. Následně je provedeno několik experimentů, které mají za úkol srovnat tyto dvě metody. Tyto experimenty jsou vyhodnoceny tak, že je možné pozorovat, které testovací úlohy dokáže lépe vyřešit člověk, aby následně bylo možné tyto poznatky použít ke zlepšení funkce automatického systému. V závěru práce je takovýto návrh na zlepšení automatického systému předveden a otestován. Testování proběhlo úspěšně a byla zaznamenána vyšší přesnost při vyhodnocování. Takový výsledek tedy může být užitý v dalších výzkumech a umožnit tak další vývoj v oblasti automatického rozpoznávání mluvčích.
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Artificial neural network RCE
Maceček, Aleš ; Klusáček, Jan (referee) ; Jirsík, Václav (advisor)
This paper is focused on an artificial neural network RCE, especially describing the topology, properties and learning algorithm of the network. This paper describes program uTeachRCE developed for learning the RCE network and program RCEin3D, which is created to visualize the RCE network in 3D space. The RCE network is compared with a multilayer neural network with a learning algorithm backpropagation in the practical application of recognition letters. For a descriptions of the letters were chosen moments invariant to rotation, translation and scaling image.
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Face Reader
Bučko, Peter ; Juránek, Roman (referee) ; Beran, Vítězslav (advisor)
This thesis deals with computer face recognition. Methods of Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Elastic Bunch Graph Matching (EBGM) are described here. Aim of this thesis is creation of a demonstration aplication for a face recognition. Moreover I test PCA and LDA methods to find out, how accurate it can be and how can be affected by changing of parameters, such as size of a database and picture count per person.
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