scholarly journals Automated Reconstruction of Parametric BIM for Bridge Based on Terrestrial Laser Scanning Data

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Guocheng Qin ◽  
Yin Zhou ◽  
Kaixin Hu ◽  
Daguang Han ◽  
Chunli Ying
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Facility Management ◽  
Information Modeling ◽  
Geometric Features ◽  
Unit Structure ◽  
Point Cloud Segmentation ◽  
Reconstruction Quality ◽  
Building Information

Building information modeling (BIM) in industrialized bridge construction is usually performed based on initial design information. Differences exist between the model of the structure and its actual geometric dimensions and features due to the manufacturing, transportation, hoisting, assembly, and load bearing of the structure. These variations affect the construction project handover and facility management. The solutions available at present entail the use of point clouds to reconstruct BIM. However, these solutions still encounter problems, such as the inability to obtain the actual geometric features of a bridge quickly and accurately. Moreover, the created BIM is nonparametric and cannot be dynamically adjusted. This paper proposes a fully automatic method of reconstructing parameterized BIM by using point clouds to address the abovementioned problems. An algorithm for bridge point cloud segmentation is developed; the algorithm can separate the bridge point cloud from the entire scanning scene and segment the unit structure point cloud. Another algorithm for extracting the geometric features of the bridge point cloud is also proposed; this algorithm is effective for partially missing point clouds. The feasibility of the proposed method is evaluated and verified using theoretical and actual bridge point clouds, respectively. The reconstruction quality of BIM is also evaluated visually and quantitatively, and the results show that the reconstructed BIM is accurate and reliable.

scholarly journals INTEGRATING TOPOGRAPHIC, PHOTOGRAMMETRIC AND LASER SCANNING TECHNIQUES FOR A SCAN-TO-BIM PROCESS

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 883-890
Author(s):  
M. Lo Brutto ◽  
E. Iuculano ◽  
P. Lo Giudice
Keyword(s):  
Laser Scanning ◽  
Building Information Modeling ◽  
Laser Scanner ◽  
Point Clouds ◽  
Parametric Modeling ◽  
Information Modeling ◽  
Survey Method ◽  
The Real ◽  
Building Information ◽  
Heritage Building

Abstract. The preservation of historic buildings can often be particularly difficult due to the lack of detailed information about architectural features, construction details, etc.. However, in recent years considerable technological innovation in the field of Architecture, Engineering, and Construction (AEC) has been achieved by the Building Information Modeling (BIM) process. BIM was developed as a methodology used mainly for new construction but, given its considerable potential, this approach can also be successfully used for existing buildings, especially for buildings of historical and architectural value. In this case, it is more properly referred to as Historic – or Heritage – Building Information Modeling (HBIM). In the HBIM process, it is essential to precede the parametric modeling phase of the building with a detailed 3D survey that allows the acquisition of all geometric information. This methodology, called Scan-to-BIM, involves the use of 3D survey techniques for the production of point clouds as a geometric “database” for parametric modeling. The Scan-to-BIM approach can have several issues relating to the complexity of the survey. The work aims to apply the Scan-to-BIM approach to the survey and modeling of a historical and architectural valuable building to test a survey method, based on integrating different techniques (topography, photogrammetry and laser scanning), that improves the data acquisition phase. The “Real Cantina Borbonica” (Cellar of Royal House of Bourbon) in Partinico (Sicily, Italy) was chosen as a case study. The work has allowed achieving the HBIM of the “Real Cantina Borbonica” and testing an approach based exclusively on a topographic constraint to merge in the same reference system all the survey data (laser scanner and photogrammetric point clouds).

A Reality Integrated BIM for Architectural Heritage Conservation

2019 ◽  
pp. 142-176
Author(s):  
Fabrizio Ivan Apollonio ◽  
Marco Gaiani ◽  
Zheng Sun
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Information Modeling ◽  
Free Form ◽  
Architectural Heritage ◽  
Ideal Model ◽  
Double Curvature ◽  
Building Information ◽  
Architectural Treatises

Building Information Modeling (BIM) has attracted wide interest in the field of documentation and conservation of Architectural Heritage (AH). Existing approaches focus on converting laser scanned point clouds to BIM objects, but laser scanning is usually limited to planar elements which are not the typical state of AH where free-form and double-curvature surfaces are common. We propose a method that combines low-cost automatic photogrammetric data acquisition techniques with parametric BIM objects founded on Architectural Treatises and a syntax allowing the transition from the archetype to the type. Point clouds with metric accuracy comparable to that from laser scanning allows accurate as-built model semantically integrated with the ideal model from parametric library. The deviation between as-built model and ideal model is evaluated to determine if feature extraction from point clouds is essential to improve the accuracy of as-built BIM.

scholarly journals Topology Reconstruction of BIM Wall Objects from Point Cloud Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1800 ◽  
Author(s):  
Maarten Bassier ◽  
Maarten Vergauwen
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Evaluation Framework ◽  
Information Modeling ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Current State ◽  
Building Information ◽  
Popular Subject ◽  
Best Fit

The processing of remote sensing measurements to Building Information Modeling (BIM) is a popular subject in current literature. An important step in the process is the enrichment of the geometry with the topology of the wall observations to create a logical model. However, this remains an unsolved task as methods struggle to deal with the noise, incompleteness and the complexity of point cloud data of building scenes. Current methods impose severe abstractions such as Manhattan-world assumptions and single-story procedures to overcome these obstacles, but as a result, a general data processing approach is still missing. In this paper, we propose a method that solves these shortcomings and creates a logical BIM model in an unsupervised manner. More specifically, we propose a connection evaluation framework that takes as input a set of preprocessed point clouds of a building’s wall observations and compute the best fit topology between them. We transcend the current state of the art by processing point clouds of both straight, curved and polyline-based walls. Also, we consider multiple connection types in a novel reasoning framework that decides which operations are best fit to reconstruct the topology of the walls. The geometry and topology produced by our method is directly usable by BIM processes as it is structured conform the IFC data structure. The experimental results conducted on the Stanford 2D-3D-Semantics dataset (2D-3D-S) show that the proposed method is a promising framework to reconstruct complex multi-story wall elements in an unsupervised manner.

scholarly journals IFCWALL RECONSTRUCTION FROM UNSTRUCTURED POINT CLOUDS

2018 ◽  
Vol IV-2 ◽  
pp. 33-39 ◽  
Author(s):  
M. Bassier ◽  
R. Klein ◽  
B. Van Genechten ◽  
M. Vergauwen
Keyword(s):  
Point Cloud ◽  
Input Data ◽  
Initial Point ◽  
Point Clouds ◽  
Information Modeling ◽  
Point Cloud Data ◽  
Ongoing Research ◽  
Cloud Data ◽  
Building Information ◽  
Wall Geometry

The automated reconstruction of Building Information Modeling (BIM) objects from point cloud data is still ongoing research. A key aspect is the creation of accurate wall geometry as it forms the basis for further reconstruction of objects in a BIM. After segmenting and classifying the initial point cloud, the labelled segments are processed and the wall topology is reconstructed. However, the preocedure is challenging due to noise, occlusions and the complexity of the input data.<br>In this work, a method is presented to automatically reconstruct consistent wall geometry from point clouds. More specifically, the use of room information is proposed to aid the wall topology creation. First, a set of partial walls is constructed based on classified planar primitives. Next, the rooms are identified using the retrieved wall information along with the floors and ceilings. The wall topology is computed by the intersection of the partial walls conditioned on the room information. The final wall geometry is defined by creating IfcWallStandardCase objects conform the IFC4 standard. The result is a set of walls according to the as-built conditions of a building. The experiments prove that the used method is a reliable framework for wall reconstruction from unstructured point cloud data. Also, the implementation of room information reduces the rate of false positives for the wall topology. Given the walls, ceilings and floors, 94% of the rooms is correctly identified. A key advantage of the proposed method is that it deals with complex rooms and is not bound to single storeys.

scholarly journals Method for clustering and identification of objects in laser scanning point clouds using dynamic logic

2021 ◽  
Author(s):  
Yevgeny Milanov ◽  
Vladimir Badenko ◽  
Vladimir Yadykin ◽  
Leonid Perlovsky
Keyword(s):  
Field Theory ◽  
Laser Scanning ◽  
Dynamic Logic ◽  
Point Clouds ◽  
Information Modeling ◽  
Digital Data ◽  
Neural Modeling ◽  
Multiple Sources ◽  
Building Information ◽  
Spatial Coordinates

Abstract Today there is a gap between a presence of various new equipment on the market which provides streams of various digital data about the environment, in particular in the form of laser scanning point clouds, and the lack of adequate efficient methods and software for information extraction from such data. A solution to the problem of bridging this gap is proposed on the basis of neural modeling field theory and dynamic logic (DL). We present a DL-based method of extracting and analyzing information from hybrid point clouds, which include not only spatial coordinates and intensity, but also the color of each point, and can be from multiple sources including terrestrial, mobile and airborne laser scanning data. The proposed method is significant for creating a fundamental theoretical basis for new application algorithms and software for many new applications, including building information modeling, “smart city” environment, etc. The proposed method is fairly new to solving various problems related to extracting semantically rich information from a nontraditional type of digital data, especially hybrid point clouds created from laser scanning. This method will allow to significantly expand the existing boundaries of knowledge in the field of extraction and analysis of information from various digital data, because neural modeling field theory and DL can improve the performance of relevant calculations and close the existing gap in analysis of digital images.

scholarly journals MLS POINT CLOUD SEGMENTATION BASED ON FEATURE POINTS OF SCANLINES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1007-1013
Author(s):  
R. Honma ◽  
H. Date ◽  
S. Kanai
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Spatial Distance ◽  
Feature Points ◽  
Segmentation Method ◽  
Point Reduction ◽  
Point Cloud Segmentation ◽  
Edge Points ◽  
The Difference

<p><strong>Abstract.</strong> Point clouds acquired using Mobile Laser Scanning (MLS) are applied to extract road information such as curb stones, road markings, and road side objects. In this paper, we present a scanline-based MLS point cloud segmentation method for various road and road side objects. First, end points of the scanline, jump edge points, and corner points are extracted as feature points. The feature points are then interpolated to accurately extract irregular parts consisting of irregularly distributed points such as vegetation. Next, using a point reduction method, additional feature points on a smooth surface are extracted for segmentation at the edges of the curb cut. Finally, points between the feature points are extracted as flat segments on the scanline, and continuing feature points are extracted as irregular segments on the scanline. Furthermore, these segments on the scanline are integrated as flat or irregular regions. In the extraction of the feature points, neighboring points based on the spatial distance are used to avoid being influenced by the difference in the point density. Based on experiments, the effectiveness of the proposed method was indicated based on an application to an MLS point cloud.</p>

A Reality Integrated BIM for Architectural Heritage Conservation

2019 ◽  
pp. 900-934
Author(s):  
Fabrizio Ivan Apollonio ◽  
Marco Gaiani ◽  
Zheng Sun
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Information Modeling ◽  
Free Form ◽  
Architectural Heritage ◽  
Ideal Model ◽  
Double Curvature ◽  
Building Information ◽  
Architectural Treatises

Building Information Modeling (BIM) has attracted wide interest in the field of documentation and conservation of Architectural Heritage (AH). Existing approaches focus on converting laser scanned point clouds to BIM objects, but laser scanning is usually limited to planar elements which are not the typical state of AH where free-form and double-curvature surfaces are common. We propose a method that combines low-cost automatic photogrammetric data acquisition techniques with parametric BIM objects founded on Architectural Treatises and a syntax allowing the transition from the archetype to the type. Point clouds with metric accuracy comparable to that from laser scanning allows accurate as-built model semantically integrated with the ideal model from parametric library. The deviation between as-built model and ideal model is evaluated to determine if feature extraction from point clouds is essential to improve the accuracy of as-built BIM.

A Reality Integrated BIM for Architectural Heritage Conservation

2017 ◽  
pp. 31-65 ◽  
Author(s):  
Fabrizio Ivan Apollonio ◽  
Marco Gaiani ◽  
Zheng Sun
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Information Modeling ◽  
Free Form ◽  
Architectural Heritage ◽  
Ideal Model ◽  
Double Curvature ◽  
Building Information ◽  
Architectural Treatises

Building Information Modeling (BIM) has attracted wide interest in the field of documentation and conservation of Architectural Heritage (AH). Existing approaches focus on converting laser scanned point clouds to BIM objects, but laser scanning is usually limited to planar elements which are not the typical state of AH where free-form and double-curvature surfaces are common. We propose a method that combines low-cost automatic photogrammetric data acquisition techniques with parametric BIM objects founded on Architectural Treatises and a syntax allowing the transition from the archetype to the type. Point clouds with metric accuracy comparable to that from laser scanning allows accurate as-built model semantically integrated with the ideal model from parametric library. The deviation between as-built model and ideal model is evaluated to determine if feature extraction from point clouds is essential to improve the accuracy of as-built BIM.

scholarly journals System analysis of the quality of meshes in HBIM

2018 ◽  
Vol 170 ◽  
pp. 03033 ◽  
Author(s):  
Elizaveta Fateeva ◽  
Vladimir Badenko ◽  
Alexandr Fedotov ◽  
Ivan Kochetkov
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
System Analysis ◽  
Point Clouds ◽  
Rational Solutions ◽  
Historical Building ◽  
Architectural Styles ◽  
Architectural Features ◽  
Building Information

Historical Building Information Modelling (HBIM) is nowadays used as a means to collect, store and preserve information about historical buildings and structures. The information is often collected via laser scanning. The resulting point cloud is manipulated and transformed into a polygon mesh, which is a type of model very easy to work with. This paper looks at the problems associated with creating mesh out of point clouds depending on various characteristics in context of façade reconstruction. The study is based on a point cloud recorded via terrestrial laser scanning in downtown Bremen, Germany that contains buildings completed in a number of different architectural styles, allowing to extract multiple architectural features. Analysis of meshes' quality depending on point cloud density was carried out. Conclusions were drawn as to what the rational solutions for effective surface extraction can be for each individual building in question. Recommendations on preprocessing of point clouds were given.

scholarly journals The use of Terrestrial Laser Scanning for the purposes of preparing technical documentation in BIM technology

2018 ◽  
Vol 17 (3) ◽  
pp. 189-199
Author(s):  
Łukasz Uchański ◽  
Krzysztof Karsznia
Keyword(s):  
Reverse Engineering ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Facility Management ◽  
Technical Documentation ◽  
Building Information ◽  
Data Capturing ◽  
Interactive 3D ◽  
Full Design

Building Information Modelling (BIM) is becoming an increasingly popular solution used both for investment and for reverse engineering aimed at restoring of the original documentation of existing facilities. The reconstruction of an object including its full design properties in an interactive 3D environment makes it possible to carry out structural (including SMH – structural health monitoring) and strength analyses, as well as to provide the effi cient facility management (setting out essential parameters and conducting necessary repairs). This paper aims to assess the laser scanning performed by using an advanced pulse data-capturing device for the development of complex BIM documentation in the Water Centre Laboratory of Warsaw University of Life Sciences – SGGW. Obtained point clouds have been used to build the model for the needs of reverse engineering. Moreover, the authors evaluated the possibility of using a particular type of laser scanner to develop and update complex BIM documentation in the process of facility management.

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