Orientador: Neucimar Jeronimo Leite / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-11T00:51:01Z (GMT). No. of bitstreams: 1 Souza_RafaelHenriqueCastanheirade_M.pdf: 1199945 bytes, checksum: 9b1286893d0b1751f7fce2dd2117cdbb (MD5) Previous issue date: 2008 / Resumo: O rastreamento automático de animais permite um estudo comportamental mais consistente e rápido do que o feito normalmente utilizando-se registro manual dos parâmetros de experimentos em biologia. O registro automático é realizado por um sistema analisador de imagens que, a partir de uma sequência contínua de quadros de um vídeo, calcula uma série de descritores associados ao movimento das cobaias. O objetivo deste trabalho é criar um sistema de rastreamento para experimentos de laboratório, levando em conta múltiplas cobaias que podem vir a sofrer oclusão. Além disso, pretende-se que o modelo de rastreamento proposto seja robusto a baixa qualidade do vídeo, além de ser geral o suficiente para ser adaptado a outros experimentos com poucas modificações / Abstract: The automatic tracking of animals allows a quicker and more consistent analysis of behaviour than the usual manual method for registering experimental parameters in biology. The automatic register of parameters is performed by a system that analyses a sequence of images and computes a number of descriptors that characterizes the behaviour of each target. Our objective is to create a framework for tracking in biology experiments, with multiple targets that may suffer occlusion. Besides, we intend to create a framework that can deal with low-quality videos and capable of being adapted to other classes of tracking / Mestrado / Processamento de Imagens / Mestre em Ciência da Computação

[Truncated abstract] The multi-object filtering problem is a logical and fundamental generalization of the ubiquitous single-object vector filtering problem. Multi-object filtering essentially concerns the joint detection and estimation of the unknown and time-varying number of objects present, and the dynamic state of each of these objects, given a sequence of observation sets. This problem is intrinsically challenging because, given an observation set, there is no knowledge of which object generated which measurement, if any, and the detected measurements are indistinguishable from false alarms. Multi-object filtering poses significant technical challenges, and is indeed an established area of research, with many applications in both military and commercial realms. The new and emerging approach to multi-object filtering is based on the formal theory of random finite sets, and is a natural, elegant and rigorous framework for the theory of multiobject filtering, originally proposed by Mahler. In contrast to traditional approaches, the random finite set framework is completely free of explicit data associations. The random finite set framework is adopted in this dissertation as the basis for a principled and comprehensive study of multi-object filtering. The premise of this framework is that the collection of object states and measurements at any time are treated namely as random finite sets. A random finite set is simply a finite-set-valued random variable, i.e. a random variable which is random in both the number of elements and the values of the elements themselves. Consequently, formulating the multiobject filtering problem using random finite set models precisely encapsulates the essence of the multi-object filtering problem, and enables the development of principled solutions therein. '...' The performance of the proposed algorithm is demonstrated in simulated scenarios, and shown at least in simulation to dramatically outperform traditional single-object filtering in clutter approaches. The second key contribution is a mathematically principled derivation and practical implementation of a novel algorithm for multi-object Bayesian filtering, based on moment approximations to the posterior density of the random finite set state. The performance of the proposed algorithm is also demonstrated in practical scenarios, and shown to considerably outperform traditional multi-object filtering approaches. The third key contribution is a mathematically principled derivation and practical implementation of a novel algorithm for multi-object Bayesian filtering, based on functional approximations to the posterior density of the random finite set state. The performance of the proposed algorithm is compared with the previous, and shown to appreciably outperform the previous in certain classes of situations. The final key contribution is the definition of a consistent and efficiently computable metric for multi-object performance evaluation. It is shown that the finite set theoretic state space formulation permits a mathematically rigorous and physically intuitive construct for measuring the estimation error of a multi-object filter, in the form of a metric. This metric is used to evaluate and compare the multi-object filtering algorithms developed in this dissertation.

Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Rusell M. Mersereau; Committee Member: Biing Hwang (Fred) Juang; Committee Member: Christopher E. Heil; Committee Member: Georgia Vachtsevanos; Committee Member: James H. McClellan. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Orientador: Janito Vaqueiro Ferreira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-16T19:38:32Z (GMT). No. of bitstreams: 1 Vitor_GiovaniBernardes_M.pdf: 6258094 bytes, checksum: fbd34947eb1efdce50b97b27f56c1920 (MD5) Previous issue date: 2010 / Resumo: O sistema de visão computacional é bastante útil em diversas aplicações de veículos autônomos, como em geração de mapas, desvio de obstáculos, tarefas de posicionamento e rastreamento de alvos. Além disso, a visão computacional pode proporcionar um ganho significativo na confiabilidade, versatilidade e precisão das tarefas robóticas, questões cruciais na maioria das aplicações reais. O presente trabalho tem como objetivo principal o desenvolvimento de uma metodologia de controle servo visual em veículos robóticos terrestres para a realização de rastreamento e perseguição de um alvo. O procedimento de rastreamento é baseado na correspondência da região alvo entre a seqüência de imagens, e a perseguição pela geração do movimento de navegação baseado nas informações da região alvo. Dentre os aspectos que contribuem para a solução do procedimento de rastreamento proposto, considera-se o uso das técnicas de processamento de imagens como filtro KNN, filtro Sobel, filtro HMIN e transformada Watershed que unidas proporcionam a robustez desejada para a solução. No entanto, esta não é uma técnica compatível com sistema de tempo real. Deste modo, tais algoritmos foram modelados para processamento paralelo em placas gráficas utilizando CUDA. Experimentos em ambientes reais foram analisados, apresentando diversos resultados para o procedimento de rastreamento, bem como validando a utilização das GPU's para acelerar o processamento do sistema de visão computacional / Abstract: The computer vision system is useful in several applications of autonomous vehicles, such as map generation, obstacle avoidance tasks, positioning tasks and target tracking. Furthermore, computer vision can provide a significant gain in reliability, versatility and accuracy of robotic tasks, which are important concerns in most applications. The present work aims at the development of a visual servo control method in ground robotic vehicles to perform tracking and follow of a target. The procedure for tracking is based on the correspondence between the target region sequence of images, and persecution by the generation of motion based navigation of information from target region. Among the aspects that contribute to the solution of the proposed tracking procedure, we consider the use of imaging techniques such as KNN filter, Sobel filter, HMIN filter and Watershed transform that together provide the desired robustness for the solution. However, this is not a technique compatible with real-time system. Thus, these algorithms were modeled for parallel processing on graphics cards using CUDA. Experiments in real environments were analyzed showed different results for the procedure for tracking and validating the use of GPU's to accelerate the processing of computer vision system / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Orientador: Janito Vaqueiro Ferreira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-20T14:52:32Z (GMT). No. of bitstreams: 1 HernandezBeleno_RubenDario_M.pdf: 6591392 bytes, checksum: fd4c66b4e3769739bb1a4283c418d2d8 (MD5) Previous issue date: 2012 / Resumo: Com o avanço da tecnologia refletida nos sistemas eletrônicos e de computação, os métodos do controle de trajetória no sistema de navegação se tornaram importantes nas diversas aplicações de veículos autônomos, como na geração de mapas, desvio de obstáculos e tarefas de posicionamento. Além disso, o controle pode proporcionar um ganho significativo na confiabilidade, versatilidade e precisão das tarefas robóticas, questões cruciais na maioria das aplicações reais. O presente trabalho tem como objetivo principal apresentar a criação de um veículo autônomo em escala. Para tanto foi desenvolvido um sistema de função sensorial que provê informações sobre a posição e orientação do carro a partir de quatro sistemas sensoriais como GPS, acelerômetro, giroscópio e a bussola (IMU), para que o veículo autônomo possa realizar a rota corretamente, de forma eficiente e segura. Neste projeto foi desenvolvido um software que integra os sistemas de controle e de sensoriamento. Além disso, foi projetado um módulo que controla a posição e orientação do veículo. O robô antes de realizar a manobra calcula a distância mínima relacionada ao próximo ponto da coordenada planejada para trocar sua referência de trajetória satisfazendo a orientação do caminho e do veículo. Para fins de avaliação, foram realizados experimentos em ambientes reais onde o carro percorre um conjunto determinado de coordenadas geográficas sem nenhuma intervenção humana, apresentando resultados do seguimento de trajetórias proposto e validando os sistemas sensoriais, além do algoritmo de controle projetado / Abstract: As electronic and computational systems technology advances, the use of path control methods in navigation systems become very important for different autonomous vehicles applications such as generating maps, avoiding obstacles and carrying out positioning tasks. In addition, controls can help increase the reliability, versatility and precision level of programmed tasks, which is exceedingly significant regarding real applications. The first aim of this work is to present the creation of an autonomous scale vehicle. We have developed a sensor system that provides information about the vehicle's position and orientation through four sensor systems such as gps, accelerometer, gyroscope and compass so that it can effectively and safely cover the right route. This project developed a software, which integrates the control and sensors systems. In addition, a control module was projected for the positioning and orientation of the vehicle. Before the robot turns to any direction, it calculates the minimal distance to the next step of the programmed coordinate, in order to change its own referenced trajectory, satisfying the orientation of the trajectory and the vehicle. For the task validation were done experiments in real life scenarios, where the vehicle follows a determined group of geo-coordinates without any human intervention, presenting results of the purposed following trajectories, validating the sensors systems and the control algorithm / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Šiame baigiamajame darbe apžvelgtos dulkių sprogimų atsiradimo priežastys bei sprogimų plitimų mechanizmas. Aprašyti sprogimų žemės ūkio įmonėse padariniai. Aptartos techninės priemonės, įgalinančias lokalizuoti pirminius silpnus dulkių sprogimus ir taip išvengiant stiprių, griaunamosios jėgos sprogimų. Išanalizuotos ugnį užtveriančių ir technologinių universaliųjų sklendžių tiesiaeiges elektros pavaros. Naudojant programinį modeliavimo paketą Matlab Simulink sudarytas universaliosios sklendės tiesiaeigės pavaros modelis ir gautos dinaminių charakteristikų imitacijos kreives. Naudojant programinį paketą SolidWorks sumodeliuota universalioji sklendė ir gauta smūginės bangos slėgio veikiamo sklendės judamojo elemento deformacija ir judamojo elemento deformacija, kai induktoriaus aktyviojoje zonoje įtaisyti papildomi atraminiai guoliai. Baigiamojo darbo pabaigoje pateiktos išvados ir pasiūlymai. / The final work of master analyses the causes of dust explosions and explosions spread mechanism. A short overview of the explosions effects in the agro - industry is presented. Technical devices enabling the localization of primary weak dust explosions and so avoiding the strong, destructive force explosions are discussed. Fire blocking and universal linear electric drives are analyzed. Using software package Matlab Simulink model of universal linear electric drive is created and dynamic characteristics are gained. Using software package SolidWorks model of universal linear electric drive is created and valves mobile element deformation and deformation of the mobile element, when there are installed additional supporting bearings in the inductor active zone are obtained when mobile element is affected by the pressure of the explosion wave. Concluding part presents inferences and suggestions.

This thesis represents Bayesian joint audio-visual tracking for the 3D locations of multiple people and a current speaker in a real conference environment. To achieve this objective, it focuses on several different research interests, such as acoustic-feature detection, visual-feature detection, a non-linear Bayesian framework, data association, and sensor fusion. As acoustic-feature detection, time-delay-of-arrival~(TDOA) estimation is used for multiple source detection. Localization performance using TDOAs is also analyzed according to different configurations of microphones. As a visual-feature detection, Viola-Jones face detection is used to initialize the locations of unknown multiple objects. Then, a corner feature, based on the results from the Viola-Jones face detection, is used for motion detection for robust objects. Simple point-to-line correspondences between multiple cameras using fundamental matrices are used to determine which features are more robust. As a method for data association and sensor fusion, Monte-Carlo JPDAF and a data association with IPPF~(DA-IPPF) are implemented in the framework of particle filtering. Three different tracking scenarios of acoustic source tracking, visual source tracking, and joint acoustic-visual source tracking are represented using the proposed algorithms. Finally the real-time implementation of this joint acoustic-visual tracking system using a PC, four cameras, and six microphones is addressed with two parts of system implementation and real-time processing.