Building detection in an urban area using lidar data and QuickBird imagery

Chen, Lei; Zhao, Shuang; Han, Wenquan; Li, Yun

doi:10.1080/01431161.2012.659355

Cited by 41 publications

(43 citation statements)

References 9 publications

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“…Os pontos dos dados LASER considerados acima do terreno, próximos a retas longas de contornos de telhados, são utilizados para gerar planos de telhados iniciais e para selecionar as demais retas que compõem cada telhado de edifício. Em Chen et al (2012) é proposto um método para detecção de edifícios com uso de dados LASER e imagem QuickBird. Os dados LASER são utilizados para gerar um MDSn (Modelo Digital de Superfície normalizado) e, assim serem obtidos os candidatos a representar edifícios, em seguida, a vegetação é filtrada com base em informações da imagem.…”

Section: Introductionunclassified

Refinamento Geométrico De Contornos E Cumeeiras De Telhados De Edifícios Extraídos De Dados Laser Com Uso De Imagem Aérea

Marcato¹,

Póz²

2014

Bol. Ciênc. Geod.

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RESUMONesse artigo é proposto um método para refinar geometricamente telhados 3D extraídos dos dados LASER com o uso de uma imagem aérea de alta-resolução e modelos de campo aleatório de Markov (MRF -Markov Random Field). Para tanto, uma descrição MRF para agrupamento de retas é desenvolvida, assumindo que cada lado de contorno e cumeeira projetado está topologicamente correto e que é necessário apenas melhorar sua acurácia. Embora a combinação de dados LASER com dados de imagem é justificada mais para o refinamento de contorno de telhado, a estrutura de cumeeiras pode dar maior robustez na descrição topológica da estrutura de telhado. O modelo MRF é formulado com base em relações (de comprimento, proximidade e orientação) entre as retas extraídas da imagem e o polígono projetado e, também, em injunções de retangularidade e quina. A função de energia associada à descrição MRF é minimizada via algoritmo genético, resultando em um agrupamento de retas para cada telhado. Finalmente, o agrupamento de retas é topologicamente reconstruído baseando-se na topologia do correspondente polígono projetado no espaço imagem. Os resultados obtidos foram satisfatórios. Esse método foi capaz de fornecer polígonos de telhado refinados em

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Section: Introductionunclassified

Refinamento Geométrico De Contornos E Cumeeiras De Telhados De Edifícios Extraídos De Dados Laser Com Uso De Imagem Aérea

Marcato¹,

Póz²

2014

Bol. Ciênc. Geod.

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“…Huang et al (15) proposed a classification method to urban area by fusion processing using point clouds and high-resolution images of RGB bands. As plants are very sensitive towards infrared wavelengths, the infrared images are used to assist the building region detection (6,8,16). In Chen et al (6) and Sohn and Dowman (16), the authors first extract a Digital Terrain Model from point clouds.…”

Section: Building Region Detectionmentioning

confidence: 99%

“…As plants are very sensitive towards infrared wavelengths, the infrared images are used to assist the building region detection (6,8,16). In Chen et al (6) and Sohn and Dowman (16), the authors first extract a Digital Terrain Model from point clouds. Then, the normalized difference vegetation index (NDVI) is calculated using infrared image data.…”

Section: Building Region Detectionmentioning

confidence: 99%

Building reconstruction from airborne laser scanning data

Huang

2013

Geo-spatial Information Science

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The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas. The airborne laser scanning technique provides new opportunities for building model reconstruction. Despite many investigations on building reconstruction using point clouds, there are still many unresolved problems that need further research, especially fully automatic methods and intelligent user-friendly operations. This article surveys the methods, tools and problems of building model reconstruction using point clouds data. The article also points out some important but unnoticed problems in building reconstruction according to our previous experience. We hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.

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“…Many methods of this category are found in the literature, as e.g. in Haala and Brenner (1999), Sohn and Dowman (2003), Jaw and Cheng et al (2008), Kim andHabib (2009), Chen andZhao (2012), Awrangjeb et al (2013), and Gilani et al (2015). This paper proposes a method for extracting groups of straight lines that represent roof boundaries and roof ridgelines from high-resolution aerial images using corresponding ALS-derived roof polyhedrons as initial approximations.…”

Section: Introductionmentioning

confidence: 99%

Extraction of Roof Lines From High-Resolution Images by a Grouping Method

Póz

Fernandes

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper proposes a method for extracting groups of straight lines that represent roof boundaries and roof ridgelines from highresolution aerial images using corresponding Airborne Laser Scanner (ALS) roof polyhedrons as initial approximations. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundaries of a building are extracted from the aerial image. Second, a group of straight lines that represent roof boundaries and roof ridgelines of a selected building is obtained through the optimization of a Markov Random Field (MRF)-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90 o ). Experimental results are presented and discussed in this paper.

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Building detection in an urban area using lidar data and QuickBird imagery

Cited by 41 publications

References 9 publications

Refinamento Geométrico De Contornos E Cumeeiras De Telhados De Edifícios Extraídos De Dados Laser Com Uso De Imagem Aérea

Refinamento Geométrico De Contornos E Cumeeiras De Telhados De Edifícios Extraídos De Dados Laser Com Uso De Imagem Aérea

Building reconstruction from airborne laser scanning data

Extraction of Roof Lines From High-Resolution Images by a Grouping Method

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