Extração semiautomática de contornos de telhado de edifícios com base em snakes e programação dinâmica

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

Método monoscópico para a determinação automática da altura de edifícios em fotografias aéreas

This paper proposes a monoscopic method for automatic determination of building's heights in digital photographs areas, based on radial displacement of points in the plan image and geometry at the time the photo is obtained. Determination of the buildings' heights can be used to model the surface in urban areas, urban planning and management, among others. The proposed methodology employs a set of steps to detect arranged radially from the system of photogrammetric coordinates, which characterizes the lateral edges of buildings present in the photo. In a first stage is performed the reduction of the searching area through detection of shadows projected by buildings, generating sub-images of the areas around each of the detected shadow. Then, for each sub-image, the edges are automatically extracted, and tests of consistency are applied for it in order to be characterized as segments of straight arranged radially. Next, with the lateral edges selected and the knowledge of the flight height, the buildings' heights can be calculated. The experimental results obtained with real images showed that the proposed approach is suitable to perform the automatic identification of the buildings height in digital images.

Predição de sombras de edifícios sobre vias urbanas com base em modelos digitais de elevações e dados de imagens aéreas de alta resolução

This research presents a methodology for prediction of building shadows cast on urban roads existing on high-resolution aerial imagery. Shadow elements can be used in the modeling of contextual information, whose use has become more and more common in image analysis complex processes. The proposed methodology consists in three sequential steps. First, the building roof contours are manually extracted from an intensity image generated by the transformation of a digital elevation model (DEM) obtained from airborne laser scanning data. In similarly, the roadside contours are extracted, now from the radiometric information of the laser scanning data. Second, the roof contour polygons are projected onto the adjacent roads by using the parallel projection straight lines, whose directions are computed from the solar ephemeris, which depends on the aerial image acquisition time. Finally, parts of shadow polygons that are free from building perspective obstructions are determined, given rise to new shadow polygons. The results obtained in the experimental evaluation of the methodology showed that the method works properly, since it allowed the prediction of shadow in high-resolution imagery with high accuracy and reliability.

Uso de dados fotogramétricos no refinamento geométrico de contornos de telhados de edifícios extraídos de dados laser

In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the 3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that, the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations ( relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, 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 preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.

Determinação automática da altura de edifícios em imagens aéreas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Predição de sombras de edifícios sobre vias urbanas com base em um modelo digital de elevações e dados de imagens aéreas de alta-resolução

Pós-graduação em Ciências Cartográficas - FCT

Análise de pavimentos de edifícios através de uma formulação do método dos elementos de contorno baseada nas hipóteses de Reissner

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo numérico para a determinação das pressões devidas à ação do vento em edifícios industriais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo das ligações entre pilares de concreto e alvenaria cerâmica de vedação

Pós-graduação em Engenharia Civil - FEIS

Inclusão de pilares numa formulação do método dos elementos de contorno para análise linear de pavimentos de edifícios

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

Valores de referência de cortisol salivar para a avaliação adrenal em crianças menores de três anos, sem patologias

Pós-graduação em Pediatria - FMB

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise dos Sinais dos Ruídos Articulares das Patologias Discais da Articulação Temporomandibular

Pós-graduação em Engenharia Mecânica - FEG

Variações de normalidade e patologias bucais em crianças com deficiência, assistidas em um Centro Odontológico Especializado do Brasil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)