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Journal ArticleDOI

Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques

TL;DR: This article surveys techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs and outlines the main methods used by these algorithms for representing knowledge about shape, identity, and relationships.
About: This article is published in Automation in Construction.The article was published on 2010-11-01. It has received 789 citations till now. The article focuses on the topics: Information model & Computer Aided Design.
Citations
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Journal ArticleDOI
TL;DR: Results show scarce BIM implementation in existing buildings yet, due to challenges of (1) high modeling/conversion effort from captured building data into semantic BIM objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in B IM occurring inexisting buildings.

1,499 citations

Journal ArticleDOI
TL;DR: The performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional mapping data and its execution for the generation of 3D point clouds from digital mobile images is presented.

661 citations


Cites result from "Automatic reconstruction of as-buil..."

  • ...Several recent and promising studies, including [37–41], show that 3D point clouds acquired by laser scanners, video or photo cameras positioned on the ground can be successfully converted to object models....

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Journal ArticleDOI
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Abstract: Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

660 citations


Cites background from "Automatic reconstruction of as-buil..."

  • ...As discussed in [74], BIMs constructed from aCADmodel do not often capture details of a facility as it was actually built....

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Journal ArticleDOI
Robert Eadie1, Mike Browne1, Henry Odeyinka1, Clare McKeown1, Sean McNiff 
TL;DR: This research demonstrates via 92 responses from a sample of BIM users that collaboration aspects produce the highest positive impact and is most often used in the early stages with progressively less use in the latter stages.

586 citations


Cites background from "Automatic reconstruction of as-buil..."

  • ...[56] demonstrate how a Multi-Disciplinary BIM Model (MDM) can be used for as-built purposes....

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Journal ArticleDOI
TL;DR: A method to automatically convert the raw 3D point data from a laser scanner positioned at multiple locations throughout a facility into a compact, semantically rich information model that is capable of identifying and modeling the main visible structural components of an indoor environment despite the presence of significant clutter and occlusion.

576 citations


Cites methods from "Automatic reconstruction of as-buil..."

  • ...process, typically using data from laser scanners as input (Figure 1) [1]....

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References
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Proceedings ArticleDOI
14 Jun 2006
TL;DR: An overview of the ASDMCon project, its 4D visualization environment, and the 3D segmentation and recognition strategies that are being employed to automate defect detection are presented.
Abstract: Techniques for three dimensional (3D) imaging and analysis of as-built conditions of buildings are gaining acceptance in the Architecture, Engineering, and Construction (AEC) community. Early detection of defects on construction sites is one domain where these techniques have the potential to revolutionize an industry, since construction defects can consume a significant portion of a project?s budget. The ASDMCon project is developing methods to aid site managers in detecting and managing construction defects using 3D imaging and other advanced sensor technologies. This paper presents an overview of the project, its 4D visualization environment, and the 3D segmentation and recognition strategies that are being employed to automate defect detection.

37 citations

01 Jan 2007
TL;DR: In this article, two approaches are proposed to increase the geometric detail of facades. One approach is based on a planar mapping of point clouds, called LASERMAP, the other is based based on cell decomposition.
Abstract: For tasks such as the generation of realistic visualizations from pedestrian viewpoints in virtual reality and multimedia applications, urban models extracted from airborne data are too coarse and therefore have to be refined. Within the paper, terrestrial LIDAR data as well as facade imagery is used to increase the quality and amount of detail for the respective 3D building models. These models, typically available from airborne data collection, provide a-priori information, which can be integrated efficiently both for the georeferencing of the terrestrial data and the subsequent geometric and visual enhancement. We introduce two approaches to increase the geometric detail of facades. One approach is based on a planar mapping of point clouds, called LASERMAP, the other is based on cell decomposition.

35 citations


"Automatic reconstruction of as-buil..." refers background or methods in this paper

  • ...use density-based edge detection to find vertical and horizontal lines in the depth map of a building façade followed by a classification of the resulting rectangles as window or non-window [11]....

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  • ...This fact allowswindow and door openings to be modeled by fitting geometric primitives to the boundaries of holes in wall surfaces [11,74]....

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  • ...More recent work has begun to focus on modeling details, such aswindow and door openings on building façades [11,74]....

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Dissertation
01 Jul 2003
TL;DR: New techniques for improving the structural quality of automatically-acquired architectural 3D models using a probabilistic technique (RANSAC) and a numerical algorithm to optimise the position and orientations of the features taking constraints into account are presented.
Abstract: This doctoral thesis presents new techniques for improving the structural quality of automatically-acquired architectural 3D models. Common architectural properties such as parallelism and orthogonality of walls and linear structures are exploited. The locations of features such as planes and 3D lines are extracted from the model by using a probabilistic technique (RANSAC). The relationships between the planes and lines are inferred automatically using a knowledge-based architectural model. A numerical algorithm is then used to optimise the position and orientations of the features taking constraints into account. Small irregularities in the model are removed by projecting the irregularities onto the features. Planes and lines in the resulting model are therefore aligned properly to each other, and so the appearance of the resulting model is improved. Our approach is demonstrated using noisy data from both synthetic and real scenes.

35 citations


"Automatic reconstruction of as-buil..." refers background or methods in this paper

  • ...Prior knowledge about component geometry, such as the diameter of a column, can be used to constrain the modeling process [16], or the characteristics of known components may be kept in a standard component library....

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  • ...Algorithms that use semantic networks for object recognition use graphs to encode the semantic network as well as the topological and directional relationships in the scene [16,68]....

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  • ...Usually, such a knowledgemodel is represented by a semantic net [16,68]....

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  • ...During the recognition process, if a surface is recognized as “floor,” then the algorithm will identify that the valid semantic labels of a surface orthogonal to it can only be “wall” or “door,” but not “ceiling,” thereby reducing the search space [16]....

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  • ...For example, the semantic network methods for recognizing components using context work well for simple examples of hallways and barren, rectangular rooms [16,68], but how would they handle spaces with complex geometries and clutter, such as an office or a bathroom? In Section 7, we identified and discussed a number of technology gaps in automated as-built BIM creation capabilities....

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01 Jun 1986
TL;DR: A general approach has been developed for processing range images to obtain a high-quality, rich (information-preserving), accurate, intermediate-level description consisting of graph surface primitives, the associated segmented regions, and their bounding edges.
Abstract: Perception of surfaces plays a fundamental role in three-dimensional object recognition and image understanding. A range image explicitly represents the surfaces of objects in a given field of view as an array of depth values. Previous research in range image understanding has limited itself to extensions of edge-based intensity image analysis or to interpretations in terms of polyhedra, generalized cylinders, quadric primitives, or convex objects. Computer vision research has demonstrated the advantages of data-driven early processing of image data. If early processing algorithms are not committed to interpretation in terms of restrictive, domain-specific, high-level models, the same algorithms may be incorporated in different applications without substantial effort. A general approach has been developed for processing range images to obtain a high-quality, rich (information-preserving), accurate, intermediate-level description consisting of graph surface primitives, the associated segmented regions, and their bounding edges. Only general knowledge about surfaces is used to compute a complete image segmentation; no object level information is involved. The early range image understanding algorithm consists primarily of a differential-geometric, visible-invariant pixel labeling method based on the sign of mean and Gaussian curvatures and an iterative region-growing method based on variable-order surface-fitting of the original image data. The high-level control logic of the current implementation is sequential, but all low-level image processes can be executed on parallel architectures. This surface-based image analysis approach has successfully segmented a wide variety of real and synthetic range images and is also shown to have significant potential for intensity image analysis. It is interesting to note that the surface and edge description algorithms use the same basic "sign-of-curvature" paradigm in different dimensions.

31 citations


"Automatic reconstruction of as-buil..." refers background in this paper

  • ...Different types of curved surfaces can be classified based on local curvature features, specifically the mean and Gaussian curvature [7]....

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Proceedings ArticleDOI
04 Oct 1999
TL;DR: The aim is to segment the triangulated surface into a small number of components, each of which approximates to part of a simple geometric shape through algorithms for curvature estimation in order to support a 'region growing' method of segmentation.
Abstract: An important aspect of reverse engineering is the production of digital representations of physical objects for CAD systems. The first stage involves taking 3D coordinate measurements for points on the surface of the object and producing in general an unstructured set of points, called a point cloud. A triangulated surface can be generated from such a point cloud, allowing copies of the original object to be manufactured. However, these triangulated surfaces generally consist of a very large number of triangles with small errors in the positions of their vertices. In many cases the original object is made up of parts of a number of simple geometric objects. Our aim is to segment the triangulated surface into a small number of components, each of which approximates to part of a simple geometric shape. We have developed algorithms for curvature estimation in order to support a 'region growing' method of segmentation.

30 citations


"Automatic reconstruction of as-buil..." refers methods in this paper

  • ...Planar surfaces are often detected using bottom-up methods, using local estimates of surface shape, such as flatness [95] or surface curvature [82], to group data into locally similar patches (Fig....

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