5 resultados para Real property--Virginia--Alexanders Island--Maps.

em Universidad Politécnica de Madrid


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Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor urbanA) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. Despite great advances on building energy performance have been achieved during the last years, available climate data is derived from weather stations placed in the outskirts of the city. Hence, urban heat island effect is not considered in energy simulations, which implies an important lack of accuracy. Since 1980's several international studies have been conducted on the urban heat island (UHI) phenomena, which modifies the atmospheric conditions of the urban centres due to urban agglomeration [1][2][3][4]. In the particular case of Madrid, multiple maps haven been generated using different methodologies during the last two decades [5][6][7]. These maps allow us to study the UHI phenomena from a wide perspective, offering however an static representation of it. Consequently a dynamic model for Madrid UHI is proposed, in order to evaluate it in a continuous way, and to be able to integrate it in building energy simulations.

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We propose a new Bayesian framework for automatically determining the position (location and orientation) of an uncalibrated camera using the observations of moving objects and a schematic map of the passable areas of the environment. Our approach takes advantage of static and dynamic information on the scene structures through prior probability distributions for object dynamics. The proposed approach restricts plausible positions where the sensor can be located while taking into account the inherent ambiguity of the given setting. The proposed framework samples from the posterior probability distribution for the camera position via data driven MCMC, guided by an initial geometric analysis that restricts the search space. A Kullback-Leibler divergence analysis is then used that yields the final camera position estimate, while explicitly isolating ambiguous settings. The proposed approach is evaluated in synthetic and real environments, showing its satisfactory performance in both ambiguous and unambiguous settings.

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We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

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Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor Urbana) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. The scope of our predictive model is defined by the heat island effect (UHI) of urban structures that compose the city of Madrid. In particular, we focus on the homogeneous areas for urban structures with the same urban and building characteristics. Data sources for the definition of such homogeneous areas were provided by previous research on the UHI of Madrid. The objective is to establish a critical analysis of climate records used for energy simulation tools, which data come from weather stations placed in decontextualized areas from the usual urban reality, where the thermal conditions differs by up to 6ºC. In this way, we intend to develop a new predictive model for the consumption and demand in buildings depending on their location, the urban structure and the associated UHI, improving the future energy rehabilitation interventions

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Esta investigación se enmarca dentro del proyecto MODIFICA (modelo predictivo - Edificios - Isla de Calor Urbano), financiado por el Programa de I + D + i Orientada a los Retos de la sociedad 'Retos Investigación' de 2013. Está dirigido a desarrollar un modelo predictivo de eficiencia energética para viviendas, bajo el efecto de isla de calor urbano (AUS) con el fin de ponerla en práctica en la evaluación de la demanda de energía real y el consumo en las viviendas. A pesar de los grandes avances que se han logrado durante los últimos años en el rendimiento energético de edificios, los archivos de tiempo utilizados en la construcción de simulaciones de energía se derivan generalmente de estaciones meteorológicas situadas en las afueras de la ciudad. Por lo tanto, el efecto de la Isla de Calor Urbano (ICU) no se considera en estos cálculos, lo que implica una importante falta de precisión. Centrado en explorar cómo incluir los fenómenos ICU, el presente trabajo recopila y analiza la dinámica por hora de la temperatura en diferentes lugares dentro de la ciudad de Madrid. Abstract This research is framed within the project MODIFICA (Predictive model - Buildings - Urban Heat Island), funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. It is aimed at developing a predictive model for dwelling energy performance under the Urban Heat Island (UHI) effect in order to implement it in the evaluation of real energy demand and consumption in dwellings. Despite great advances on building energy performance have been achieved during the last years, weather files used in building energy simulations are usually derived from weather stations placed in the outskirts of the city. Hence, Urban Heat Island (UHI) effect is not considered in this calculations, which implies an important lack of accuracy. Focused on exploring how to include the UHI phenomena, the present paper compiles and analyses the hourly dynamics of temperature in different locations within the city of Madrid.