965 resultados para object modeling from images
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This research covers the topic of social housing and its relation to thermal comfort, so applied to an architectural and urban intervention in land situated in central urban area of Macaíba/RN, Brazil. Reflecting on the role of design and use of alternative building materials in the search for better performance is one of its main goals. The hypothesis is that by changing design parameters and choice of materials, it is possible to achieve better thermal performance results. Thus, we performed computer simulations of thermal performance and natural ventilation using computational fluid dynamics or CFD (Computational Fluid Dynamics). The presentation of the thermal simulation followed the methodology proposed in the dissertation Negreiros (2010), which aims to find the percentage of the amount of hours of comfort obtained throughout the year, while data analysis was made of natural ventilation from images generated by the images extracted from the CFD. From model building designed, was fitted an analytical framework that results in a comparison between three different proposals for dwellings housing model, which is evaluated the question of the thermal performance of buildings, and also deals with the spatial variables design, construction materials and costs. It is concluded that the final report confirmed the general hypotheses set at the start of the study, it was possible to quantify the results and identify the importance of design and construction materials are equivalent, and that, if combined, lead to gains in thermal performance potential.
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As Sociology becomes a mandatory subject in the curricular componentof Brazilian high schools, we find anopportune moment to proposals and changes in the subject and in teaching, in a general aspect. It s noticed the great importance of the role that the create imagination plays in individual s formation (BACHELARD), and it s also seen that Brazilian education system has marginalized imagination to the detriment of a unifocused scientism that sterilizes creativity, playfulness and poetry in its educational process. Nevertheless, a way of thinking redefinitions to the educational horizons of Sociology as a subject and education is upheld. An educational practice that reconnects the prosaic and the poetic, using images/songs as paths/strategies of the teaching-learning process. As for that, the school structure was used where the tutor work was done to undertake experiences that made the use of songs as strategy to facilitate/stimulate the learning of the subject Sociology in high school. From thoughts and results of this experience, plus the bibliographic studies, analysis were made. The goal of this essay is to make use and stimulate the creation of poetic images from the teaching point of view, specially the Sociology subject in high school, rethinking and searching more efficient and playful ways of approaching and building educational methods from images; stimulating the development of the Thinking Reform and the Anthropoetics of the human gender (MORIN); acknowledging that imagination is an indispensable part of our integral formation
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In this paper a methodology for automatic extraction of road segments from images with different resolutions (low, middle and high resolution) is presented. It is based on a generalized concept of lines in digital images, by which lines can be described by the centerlines of two parallel edges. In the specific case of low resolution images, where roads are manifested as entities of 1 or 2 pixels wide, the proposed methodology combines an automatic image enhancement operation with the following strategies: automatic selection of the hysteresis thresholds and the Gaussian scale factor; line length thresholding; and polygonization. In medium and high resolution images roads manifest as narrow and elongated ribbons and, consequently, the extraction goal becomes the road centerlines. In this case, it is not necessary to apply the previous enhancement step used to enhance roads in low resolution images. The results obtained in the experimental evaluation satisfied all criteria established for the efficient extraction of road segments from different resolution images, providing satisfactory results in a completely automatic way.
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Land cover mappings represent important tools for the regional planning. However, the current mappings are related to very specific purposes and, consequently, they are limited in their capacity to define the wide variety of existing types of land cover. In that context, this paper aims at developing a wide and including hierarchical classification system for land cover mapping in regional scale, which should contribute for a future standardization of classes. Besides, it is intended to test that system for a study case that contemplates the use of a classification method based on fuzzy approach, which has shown to be more appropriate than conventional approaches. Therefore, it was proposed a hierarchical classification system with three detailing levels and a study case was defined with the specification of the test area and of the classification project. Then, the georreferencing of a TM/Landsat-5 image that comprises the test area was carried out. Later, it was applied a fuzzy classification approach in the TM/Landsat-5 image, starting from images of probability for the mapped classes and an uncertainty image were generated. Finally, it was produced a conventional output that represents the thematic mapping of the test area.
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Porosity in starch consolidation casting technique is rightly related to original size and morphology of starch granules, leaving a pore structure after burning out. This work reports the results for the addition of different native potato and corn starch proportions in suspension,; with TiO(2) (rutile) powder. Gelling temperature have been defined after observation under light microscopy using a heating stage. Analysis of porous network and isolated pores have been clone from images of samples surfaces obtained by depth from focus reconstruction, revealing a qualitative correlation of pores characteristics and starches additions in suspensions, suggesting that the presence of isolated or interconnected pores can be handled by starches selection to control the amylopectin and amylose contents in slurries. Also, the analysis of porous fraction distribution shows no consistent pattern through specimens' volume according to starches in mixtures.
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Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.
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Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.
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Neste artigo construímos um entrelaçamento teórico-filosófico que tem como objetivo discutir a relação entre Modelagem Matemática e realidade do mundo cibernético. em particular, essa abrangência da realidade é evidenciada como um possível vetor de virtualização, isto é, como um aspecto que pode influenciar o modo como a problemática que envolve uma determinada situação ou entidade é compreendida. Para tanto, fazemos uma associação entre Modelagem Matemática e as transformações que envolvem os modos de ser denotados por real, possível, atual e virtual, tendo como base ilustrativa as quatro causas aristotélicas. Complementando essa associação, assumimos uma concepção de problema que permite uma consolidação entre as relações estabelecidas e, também, uma concepção de realidade que entende o mundo cibernético como uma de suas dimensões. Por fim, apresentamos um exemplo de Modelagem Matemática ocorrido em sala de aula, que visa caracterizar a realidade do mundo cibernético como um vetor de virtualização.
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The acquisition and update of Geographic Information System (GIS) data are typically carried out using aerial or satellite imagery. Since new roads are usually linked to georeferenced pre-existing road network, the extraction of pre-existing road segments may provide good hypotheses for the updating process. This paper addresses the problem of extracting georeferenced roads from images and formulating hypotheses for the presence of new road segments. Our approach proceeds in three steps. First, salient points are identified and measured along roads from a map or GIS database by an operator or an automatic tool. These salient points are then projected onto the image-space and errors inherent in this process are calculated. In the second step, the georeferenced roads are extracted from the image using a dynamic programming (DP) algorithm. The projected salient points and corresponding error estimates are used as input for this extraction process. Finally, the road center axes extracted in the previous step are analyzed to identify potential new segments attached to the extracted, pre-existing one. This analysis is performed using a combination of edge-based and correlation-based algorithms. In this paper we present our approach and early implementation results.
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This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.
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Structures transverse/sub-transverse to the shoreline have been identified and characterized on the precambrian basement outcrop on the continent adjacent to the northern Santos Basin. These structures were analyzed from images of digital elevation model SRTM 90m by extracting NW-SE lineaments that intersect the NE-SW foliation. The lineaments were selected, classified into 48 segments that extend toward offshore, and correlated with basin structures. In the basin 25 2D seismic sections, 12 well logs and data from potential methods were interpreted, identifying the key stratigraphic levels and the major structures. Structural maps of each horizon were generated. Six transfer faults (FTs) were recognized and named FT-1 to FT-6, whose extensions correspond to continental lineaments named FC1 to FC6. The FTs are related to the basin deformation and evolution. In seismic sections, these faults have lateral slip in flower structures, displacement inversions from normal at the top to reverse at the base, abrupt changes in thickness or even disappearance of the seismic reflectors. The structural map of the Basement and Top of the Rift shows control of some depocenters by faults and displacements in some areas. The maps of potential methods indicate that there are pronounced anomaly shifts in some areas, associated with FTs. Some seismic sections indicate reactivation of FTs when they intersect horizons from the basement until the most recent layers. The 3D integration of data facilitated the observation of the FT extensions in the continent discontinuity.
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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.
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Pós-graduação em Estudos Linguísticos - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA