23 resultados para Creating a digital vision
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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With the advancement of the gaming industry in the market, became evident the need for trained professionals working in this area. This paper tries to study and report the process of creating a game for professional and aspirants game developers. For this reason, throughout this monograph will describe how was the process of creating a digital game developed by students at the Universidade Estadual Paulista-UNESP Bauru. The project tries to explore current mechanical created along with an emotional storyline
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This research was developed with the goal of creating a Digital Terrain Model(DTM),through a topo-bathymetric data gathering that allows the monitoring of the fluvial dynamics of part of Guaratinguetá’s creek, where preliminary evaluations identified, in a short period of time, intense changes on its riverbed. Modern topography technics and tools were used for the data gathering, such as the use of geodesic GPS and Total Station. The DTM was primal for the project e execution of the desilting works of the researched part of the creek, being used to estimate the amount of soil to be moved. The comparison between the digital terrain models generated before and after the desilting has showed the efficiency and aplicability of this technique in the monitoring of the fluvial dynamics changes of Guaratinguetá’s creek
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.
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Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.
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Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.
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This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.
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Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.
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Pós-graduação em Comunicação - FAAC
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC