Extração e regularização de contornos de telhados de edificações a partir de dados LiDAR usando o algoritmo alpha-shape e CD-Spline
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Data
2019-04-30
Autores
Santos, Renato César dos [UNESP]
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Universidade Estadual Paulista (Unesp)
Resumo
Esta tese trata da extração e regularização automática de contornos de telhados de edificações obtidos a partir de dados LiDAR (Light Detection and Ranging) adquiridos por sistema de varredura a LASER (Light Amplification by Stimulated Emission of Radiation) aerotransportado. Em linhas gerais, dois problemas são tratados. O primeiro corresponde à determinação adaptativa do parâmetro α do algoritmo alpha-shape, utilizado na obtenção do contorno aproximado, a partir da nuvem de pontos. O segundo refere-se à regularização/modelagem dos contornos de edificações no espaço tridimensional, incluindo edificações formadas por segmentos curvos de maior complexidade. Com relação ao primeiro problema, duas abordagens foram propostas, ambas baseadas no espaçamento médio entre os pontos. A principal contribuição das abordagens propostas está ligada à determinação adaptativa de α, possibilitando minimizar a influência da variação da densidade de pontos. Para solucionar o problema ligado a regularização de contornos, uma metodologia baseada no conceito de CD-Spline (Changeable Degree Spline) foi desenvolvida. A principal contribuição do uso da CD-Spline está ligada à habilidade de modelar contornos formados por segmentos com diferentes níveis de complexidade no espaço n-dimensional, sendo esses modelados por funções polinomiais de diferentes graus. Na metodologia proposta, a função polinomial que melhor modela cada segmento é selecionada de forma automática por meio da análise estatística dos resíduos em uma abordagem iterativa. Para validar as abordagens propostas dois conjuntos de dados LiDAR foram considerados. O primeiro corresponde ao Unesp Photogrammetric Dataset de Presidente Prudente/Brasil, e o segundo corresponde aos dados de Vaihingen/Alemanha, disponibilizado pela Sociedade Alemã de Fotogrametria. Considerando a determinação do parâmetro α, as análises qualitativa e quantitativa indicaram que as abordagens propostas possibilitam minimizar a influência da variação de densidade e apresentam potencial na extração de contornos de edificações, apresentando melhores resultados quando comparado com uma abordagem mais simples, como por exemplo, o uso de um parâmetro α global. Com relação a regularização de contornos, os resultados mostraram que o método proposto pode ser aplicado na modelagem de diferentes tipos de contornos, tendo resultados satisfatórios mesmo diante de contornos formados por segmentos curvos de diferente complexidade. Além disso, a abordagem foi capaz de recuperar o contorno em regiões com oclusão, causada por vegetação, e mostrou-se robusta a conjuntos de dados com diferentes densidades.
This Doctoral dissertation deals with the automatic extraction and regularization of building roof boundaries from LiDAR (Light Detection and Ranging) data, obtained by airborne LASER (Light Amplification by Stimulated Emission of Radiation) scanning. In this context, two problems were explored. The first corresponds to the adaptive determination of the parameter α of the alpha-shape algorithm, used to extract the approximate contour, from the available point cloud. The second refers to the regularization/modeling of building boundaries in the three-dimensional space, including buildings formed by curved segments of high complexity. Regarding the first problem, two approaches were proposed, both based on average point spacing. The main contribution of the approaches is related to the adaptive determination of α, allowing to minimize the influence of the point density variation. In order to solve the problem related to boundary regularization, a method based on the concept of CD-Spline (Changeable Degree Spline) was developed. The CD-Spline has ability to model boundaries formed by segments with different levels of complexity in n-dimensional space, which are modeled by polynomial functions of different degrees. In order to select the polynomial function automatically, an iterative approach of the CD-Spline was proposed. In this methodology, the polynomial function that best models each segment is selected by means of the statistical analysis of the residuals in each iteration. Two LiDAR datasets were considered to validate the proposed approaches. The first corresponds to the Unesp Photogrammetric Dataset of Presidente Prudente/Brazil, whereas the second corresponds to Vaihingen/Germany, being made available by German Association of Photogrammetry. Considering the determination of the parameter α, the qualitative and quantitative analyzes indicated that the proposed approaches are robust to density variation and have potential in the building boundary extraction, having better results when compared to a simpler approach, for example, the use of a global parameter. With respect to boundary regularization, the results indicated that the proposed method has ability to model of different types of boundaries, having satisfactory results even in contours formed by curved segments of different complexity. In addition, the approach was able to recover the contour in occlusion regions, caused by vegetation, and was robust in different densities.
This Doctoral dissertation deals with the automatic extraction and regularization of building roof boundaries from LiDAR (Light Detection and Ranging) data, obtained by airborne LASER (Light Amplification by Stimulated Emission of Radiation) scanning. In this context, two problems were explored. The first corresponds to the adaptive determination of the parameter α of the alpha-shape algorithm, used to extract the approximate contour, from the available point cloud. The second refers to the regularization/modeling of building boundaries in the three-dimensional space, including buildings formed by curved segments of high complexity. Regarding the first problem, two approaches were proposed, both based on average point spacing. The main contribution of the approaches is related to the adaptive determination of α, allowing to minimize the influence of the point density variation. In order to solve the problem related to boundary regularization, a method based on the concept of CD-Spline (Changeable Degree Spline) was developed. The CD-Spline has ability to model boundaries formed by segments with different levels of complexity in n-dimensional space, which are modeled by polynomial functions of different degrees. In order to select the polynomial function automatically, an iterative approach of the CD-Spline was proposed. In this methodology, the polynomial function that best models each segment is selected by means of the statistical analysis of the residuals in each iteration. Two LiDAR datasets were considered to validate the proposed approaches. The first corresponds to the Unesp Photogrammetric Dataset of Presidente Prudente/Brazil, whereas the second corresponds to Vaihingen/Germany, being made available by German Association of Photogrammetry. Considering the determination of the parameter α, the qualitative and quantitative analyzes indicated that the proposed approaches are robust to density variation and have potential in the building boundary extraction, having better results when compared to a simpler approach, for example, the use of a global parameter. With respect to boundary regularization, the results indicated that the proposed method has ability to model of different types of boundaries, having satisfactory results even in contours formed by curved segments of different complexity. In addition, the approach was able to recover the contour in occlusion regions, caused by vegetation, and was robust in different densities.
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Palavras-chave
Fotogrametria, Extração de contornos de telhados, Regularização de contornos de telhados, Modelagem de contornos, Dados LiDAR, Algoritmo alpha-shape, CD-Spline, Photogrammetry, Building boundary extraction, Building roof boundary regularization, Contour modeling, LiDAR data, Alpha-shape algorithm