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Gas Cylinder Counting in Camera Images
Klos, Dominik ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
This thesis deals with an automatic counting of cylinders placed on the back of a truck using images taken by a camera mounted above the car. To achieve this goal, an SVM classifier based on HOG image descriptors has been trained to detect the cylinders. Further, a tracking method based on optical flow estimation has been designed to track the cylinders through image sequences. The result of the thesis is an application that counts bottles with precision 93,08 % placed on the truck and visualizes results of the detection.
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Recognition of Poses and Gestures
Jiřík, Leoš ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis inquires the existing methods on the field of image recognition with regards to gesture recognition. Some methods have been chosen for deeper study and these are to be discussed later on. The second part goes in for the concenpt of an algorithm that would be able of robust gesture recognition based on data acquired within the AMI and M4 projects. A new ways to achieve precise information on participants position are suggested along with dynamic data processing approaches toward recognition. As an alternative, recognition using Gaussian Mixture Models and periodicity analysis are brought in. The gesture class in focus are speech supporting gestures. The last part demonstrates the results and discusses future work.
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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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Mouse Gesture Recognition
Král, Jiří ; Zuzaňák, Jiří (referee) ; Hradiš, Michal (advisor)
This project deals with Mouse gesture recognition. Proposed system models trajectories using Hidden markov model (HMM), that models gesture as an time sequence of features. In the project there are several parametrizations analyzed and compared. The best parametrization (position normalized by center of gravity and size) reached Sensitivity of recognition of 98 %.
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Estimation of Object Parameters from Images
Přibyl, Bronislav ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
Rapid expansion of communication technologies in last decade caused increased volume of information which is beeing generated and shared by people and organisations. It is permanently harder to identify relevant content today because of absence of tools and techniques which may support mass information management. As today's media have rather multimedial character image information is even more important. This project describes software for automatic estimation of predefined object parameters from images. A C++ implementation of this algorithm is also described.
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Chord recognition
Soudek, Ondřej ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
The goal of this bachelor thesis is to create an application, that will perform a real-time analysis of a signal from electric or acoustic guitar and will recognize a chord or tone, played by user. This document contains basics of music theory and the solution of the problem, as well as the results of testing.
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Object Recognition by Means of Evolutionary Methods
Lýsek, Jiří ; Škorpil, Vladislav (referee) ; Rábová, Ivana (referee) ; Šťastný, Jiří (advisor)
This thesis deals with usage of evolutionary methods, grammatical evolution particularly in application for object recognition in an image. Basic principles of object recognition and evolutionary methods with focus on grammatical evolution are described. The core of the thesis lies in design of techniques and methods for classifier programs creation using grammatical evolution. Also the designed fitness formula is presented. In the end, created testing and development environment in Java programming language is described.
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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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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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Emotional State Recognition and Classification Based on Speech Signal Analysis
Černý, Lukáš ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis focuses on classification of emotions. Thesis deals about parameterization of sounds files by suprasegment and segment methods with regard for next used of these methods. Berlin database is used. This database includes many of sounds records with emotions. Parameterization creates files, which are divided to two parts. First part is used for training and second part is used for testing. Point of interest is self-organization network. Thesis includes Matlab´s program which can be used for parameterization of any database. Data are classified by self-organization network after parameterization. Results of hits rates are presented at the end of this diploma thesis.
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