Automatic Reconstruction of Building Façade Model from Photogrammetric Mesh Model

Zhang, Yunsheng; Zhang, Chi; Chen, Siyang; Chen, Xueye

doi:10.3390/rs13193801

Cited by 9 publications

(12 citation statements)

References 30 publications

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“…Zhang et al [44] presented an automatic reconstruction of 3-D building façade models from photogrammetric mesh models. First, the mesh model is divided into components based on contour line.…”

Section: A Geometric Abstractionmentioning

confidence: 99%

Lightweight Reconstruction of Urban Buildings: Data Structures, Algorithms, and Future Directions

Kamra

Kudeshia

ArabiNaree

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Commercial buildings as well as residential houses represent core structures of any modern day urban or semiurban areas. Consequently, 3-D models of urban buildings are of paramount importance to a majority of digital urban applications, such as city planning, 3-D mapping and navigation, video games and movies, and construction progress tracking, among others. However, current studies suggest that existing 3-D modeling approaches often involve high computational cost and large storage volumes for processing the geometric details of the buildings. Therefore, it is essential to generate concise digital representations of urban buildings from the 3-D measurements or images so that the acquired information can be efficiently utilized for various urban applications. Such concise representations, often referred to as "lightweight" models, strive to capture the details of the physical objects with less computational storage. Furthermore, lightweight models consume less bandwidth for online applications and facilitate accelerated visualizations. With many emerging digital urban infrastructure applications, lightweight reconstruction is poised to become a new area of research in the urban remote sensing community. We aim to provide a thorough review of data structures, representations, and state-of-the-art algorithms for lightweight 3-D urban reconstruction. We discuss the strengths and weaknesses of key lightweight urban reconstruction techniques, ultimately providing guidance on future research prospects to fulfill the pressing needs of urban applications.

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Section: A Geometric Abstractionmentioning

confidence: 99%

Lightweight Reconstruction of Urban Buildings: Data Structures, Algorithms, and Future Directions

Kamra

Kudeshia

ArabiNaree

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…Photogrammetry Photogrammetry commonly involves using imagery to create a depth modality from image input. For 3D building reconstruction, several studies propose using Li-DAR, aerial images, or a combination of both, as seen in [7,8]. Hu et al [9] present an approach that uses a multi-label energy minimization solution and a roof connection graph to semantically decompose and reconstruct LiDAR point clouds into complex roof structures.…”

Section: Related Workmentioning

confidence: 99%

Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery

Khomiakov¹,

Valverde²,

Reinders³

et al. 2023

Preprint

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We present a novel pipeline for learning the conditional distribution of a building roof mesh given pixels from an aerial image, under the assumption that roof geometry follows a set of regular patterns. Unlike alternative methods that require multiple images of the same object, our approach enables estimating 3D roof meshes using only a single image for predictions. The approach employs the PolyGen, a deep generative transformer architecture for 3D meshes. We apply this model in a new domain and investigate the sensitivity of the image resolution. We propose a novel metric to evaluate the performance of the inferred meshes, and our results show that the model is robust even at lower resolutions, while qualitatively producing realistic representations for out-of-distribution samples.

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“…First, the contour-based line extraction method [36,37] is used to extract line features from the oblique photogrammetric surface mesh and 3D laser point cloud. For the photogrammetric mesh model, the relative ground elevation h s of the cutting plane is given along the Z axis direction.…”

Section: Line Feature Extractionmentioning

confidence: 99%

Geometry and Topology Reconstruction of BIM Wall Objects from Photogrammetric Meshes and Laser Point Clouds

et al. 2023

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As the foundation for digitalization, building information modeling (BIM) technology has been widely used in the field of architecture, engineering, construction, and facility management (AEC/FM). Unmanned aerial vehicle (UAV) oblique photogrammetry and laser scanning have become increasingly popular data acquisition techniques for surveying buildings and providing original data for BIM modeling. However, the geometric and topological reconstruction of solid walls, which are among the most important architectural structures in BIM, is still a challenging undertaking. Due to noise and missing data in 3D point clouds, current research mostly focuses on segmenting wall planar surfaces from unstructured 3D point clouds and fitting the plane parameters without considering the thickness or 3D shape of the wall. Point clouds acquired only from the indoor space are insufficient for modeling exterior walls. It is also important to maintain the topological relationships between wall objects to meet the needs of complex BIM modeling. Therefore, in this study, a geometry and topology modeling method is proposed for solid walls in BIM based on photogrammetric meshes and laser point clouds. The method uses a kinetic space-partitioning algorithm to generate the building footprint and indoor floor plan. It classifies interior and exterior wall segments and infers parallel line segments to extract wall centerlines. The topological relationships are reconstructed and maintained to build wall objects with consistency. Experimental results on two datasets, including both photogrammetric meshes and indoor laser point clouds, exhibit more than 90% completeness and correctness, as well as centimeter-level accuracy of the wall surfaces.

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Automatic Reconstruction of Building Façade Model from Photogrammetric Mesh Model

Cited by 9 publications

References 30 publications

Lightweight Reconstruction of Urban Buildings: Data Structures, Algorithms, and Future Directions

Lightweight Reconstruction of Urban Buildings: Data Structures, Algorithms, and Future Directions

Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery

Geometry and Topology Reconstruction of BIM Wall Objects from Photogrammetric Meshes and Laser Point Clouds

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