55 resultados para Mesh generation from image data


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The efficient generation of digital surface model (DSM) from optical images has been explored for many years and the results are dependent on the project characteristics (image resolution, size of overlap between images, among others), of the image matching techniques and the computer capabilities for the image processing. The points generated from image matching have a direct impact on the quality of the DSM and, consequently, influence the need for the costly step of edition. This work aims at assessing experimentally a technique for DSM generation by matching of multiple images (two or more) simultaneously using the vertical line locus method (VLL). The experiments were performed with six images of the urban area of Presidente Prudente/SP, with a ground sample distance (GSD) of approximately 7cm. DSMs of a small area with homogeneous texture, repetitive pattern, moving objects including shadows and trees were generated to assess the quality of the developed procedure. This obtained DSM was compared to cloud points acquired by LASER (Light Amplification by Simulated Emission of Radiation) scanning as wells as with a DSM generated by Leica Photogrammetric Suite (LPS) software. The accomplished results showed that the MDS generated by the implemented technique has a geometric quality compatible with the reference models.

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Techniques of image capture have advanced along with the technologies of information and communication and unthinkable numbers of information available and imagery are stored in digital environments. The objective of this study is point out difficulties found in the construction of imagetic representations of digital resources using the instruments available for the treatment of descriptive information. The results we have the mapping of descriptive elements to digital images derived from analyzing of the schemes to guide the construction of descriptive records (AACR2R, ISBD, Graphic Materials, RDA, CDWA, CCO) and the conceptual model FRBRer. The result of this analysis conducted the conceptual model, Functional Requirements for Digital Imagetic Data RFDID to the development of more efficient ways to represent the use of imagery in order to make it available, accessible and recoverable from the data persistence descriptive, flexibility, consistency and integrity as essential requirements for the representation of the digital image.

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Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

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The research aims to propose grants for development of Municipal Plan for the Management of Organic Solid Waste generated in the municipality of Rio Claro. The research universe was composed of organic waste generators establishments (markets and grocers). From the registry of commercial establishments provided by the municipal government were identified who presented this typology, which totaled 38 establishments. In this universe the interview was conducted in 15 establishments obtained by directed sampling based on the characteristics of size, type and location. The data collected were the amount generated, disposal of waste, waste separation, collection frequency, reasons for the disposal of waste, frequency of purchase of products. From the data obtained in the field, we estimated the total generation of organic waste in this segment for the municipality. Then, the estimated costs for implementation and operation of a composting center, a way to subsidize the implementation of the management plan was carried out. We opted for the aerobic composting process by the simplicity of operation and because it is a technique already known. The average waste generation was established by tracks (size) with: stores up to 4 boxes (classified as small) generate on average 1511 kg / month, 40% of organic waste, the 5-9 boxes (small/midsize) generate on average 4338 kg / month, 35% organic and the 10 to 19 boxes (midsize) generate on average 7647 kg / month with 32% organic. In total establishments generate 105 t/ month of waste, with 35t / month of organics. 94% of establishments are in font segregation of waste into recyclable, organic and waste, indicating that the proposed management of organic waste is amenable to application without many changes in existing routine in stores. Recyclables are sent for recycling through selective collection held by the cooperative, while the organics are destined for the landfill and feed. The results indicate...

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The study of mathematical modeling assists in evaluation of the capacity of production and measurement of generation time of biogas in landfills, enabling the implantation of projects of energy generation from methane. Thus, the work aims, by simulating scenarios of potential methane generation in the landfill in Rio Claro, the use of field data from methane flow and waste grounded parameters as references for selecting values of k e L0 used to estimate methane generation model in LandGEM. As a result it was found that compared the characteristics adopted in the four scenarios recommended by the USEPA literature with those found in the landfill of Rio Claro (high amount of organic matter in the waste landed and daily practice of leachate recirculation), the scenario that apparently better represent the rate of methane generation is the scenario 01, with k = 0.7 and L0 = 96. Now, the adjustment of parameters in relation to the data field of methane flow, the value of L0 which best fits the methane generation from the landfill in Rio Claro is 150, while for k the line behavior that best represents the reality are values between 0.7 and 0.3. Regarding the parameters of the waste grounded, between the suggested values of k, 0,3 is most consistent with the intermediate level of biological degradation of the residue grounded, while L0 due to the biodegradability of the waste, a new value between 120 and 150 may be more appropriate for the study

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In this paper, a method is proposed to refine the LASER 3D roofs geometrically by using a high-resolution aerial image and Markov Random Field (MRF) models. In order to do so, a MRF description for grouping straight lines is developed, assuming that each projected side contour and ridge is topologically correct and that it is only necessary to improve its accuracy. Although the combination of laser data with data from image is most justified for refining roof contour, the structure of ridges can give greater robustness in the topological description of the roof structure. The MRF model is formulated based on relationships (length, proximity, and orientation) between the straight lines extracted from the image and projected polygon and also on retangularity and corner injunctions. The energy function associated with MRF is minimized by the genetic algorithm optimization method, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding LASER scanning polygon projected onto the image-space. The results obtained were satisfactory. This method was able to provide polygons roof refined buildings in which most of its contour sides and ridges were geometrically improved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciência da Computação - IBILCE