19 resultados para Texture Patterns
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Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.
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Dissertação de Mestrado em Engenharia Informática
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Thesis submitted for assessment with a view to obtaining the degree of Doctor of Political and Social Science of the European University Institute
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Tese de Mestrado em Engenharia Informática
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With an example taken from a late-Hauterivian series of the Lusitanian Basin (Portugal), we will demonstrate the sedimentary record of orbital pattern variations and, consequently, climate variations in an inner platform environment with patterns and isolation changes, allows us to establish 4 major orders of periodicity related to orbital components:- The large cycles ob bed thickness variation, constituted by 31-32 beds, recording the 400 ky eccentricity cycle component;- The medium cycles, represented by byndles of 8-9 beds, related to the 100 ky eccentricity cycle component; - The small cycles, of 3-5 beds, recording the 41 ky obliquity components;- The very small cycles, of 2 beds, related to the 22 ky and 26 ky precession components. The mean duration of each bed is around 11.8 ky, a number very close to that of the precession hemi-cycle. Climatic control on qualitative production is confirmed by the close relation between the bed thickness variations, the insolation variability and the variation of micritized elements concentrations.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Thesis submitted in partial fulfillment of the requirements for the Degree of Doctor of Statistics and Information Management
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Gestão de Informação
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente
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The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.