scholarly journals COMPARISON AND ASSESSMENT OF 3D REGISTRATION AND GEOREFERENCING APPROACHES OF POINT CLOUDS IN THE CASE OF EXTERIOR AND INTERIOR HERITAGE BUILDING RECORDING

2018 ◽  
Vol XLII-2 ◽  
pp. 745-751 ◽  
Author(s):  
A. Murtiyoso ◽  
P. Grussenmeyer
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
3D Registration ◽  
Technical Problems ◽  
Information Models ◽  
Geometrical Quality ◽  
Building Information ◽  
Heritage Building ◽  
Free Network

In the field of 3D heritage documentation, point cloud registration is a relatively common issue. With rising needs for Historic Building Information Models (HBIMs), this issue has become more important as it determines the quality of the data to be used for HBIM modelling. Furthermore, in the context of historical buildings, it is often interesting to document both the exterior façades as well as the interior. This paper will discuss two approaches of the registration and georeferencing of building exterior and interior point clouds coming from different sensors, namely the independent georeferencing method and the free-network registration and georeferencing. Building openings (mainly windows) were used to establish common points between the systems. These two methods will be compared in terms of geometrical quality, while technical problems in performing them will also be discussed. Furthermore, an attempt to automate some parts of the workflow using automatic 3D keypoints and features detection and matching will also be described in the paper. Results show that while both approaches give similar results, the independent approach requires less work to perform. However, the free-network method has the advantage of being able to compensate for any systematic georeferencing error on either system. As regards to the automation attempt, the use of 3D keypoints and features may reduce processing time; however correct tie point correspondence filtering remains difficult in the presence of heavy point cloud noise.

A New Kinect-Based Scanning System and its Application

2015 ◽  
Vol 764-765 ◽  
pp. 1375-1379 ◽  
Author(s):  
Cheng Tiao Hsieh
Keyword(s):  
Point Cloud ◽  
Depth Map ◽  
Bilateral Filter ◽  
Point Clouds ◽  
Digital Fabrication ◽  
Surface Model ◽  
Scanning System ◽  
3D Registration ◽  
Noise Point

This paper aims at presenting a simple approach utilizing a Kinect-based scanner to create models available for 3D printing or other digital manufacturing machines. The outputs of Kinect-based scanners are a depth map and they usually need complicated computational processes to prepare them ready for a digital fabrication. The necessary processes include noise filtering, point cloud alignment and surface reconstruction. Each process may require several functions and algorithms to accomplish these specific tasks. For instance, the Iterative Closest Point (ICP) is frequently used in a 3D registration and the bilateral filter is often used in a noise point filtering process. This paper attempts to develop a simple Kinect-based scanner and its specific modeling approach without involving the above complicated processes.The developed scanner consists of an ASUS’s Xtion Pro and rotation table. A set of organized point cloud can be generated by the scanner. Those organized point clouds can be aligned precisely by a simple transformation matrix instead of the ICP. The surface quality of raw point clouds captured by Kinect are usually rough. For this drawback, this paper introduces a solution to obtain a smooth surface model. Inaddition, those processes have been efficiently developed by free open libraries, VTK, Point Cloud Library and OpenNI.

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 ASSESSMENT OF A KEYPOINTS DETECTOR FOR THE REGISTRATION OF INDOOR AND OUTDOOR HERITAGE POINT CLOUDS

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 133-138
Author(s):  
R. Assi ◽  
T. Landes ◽  
A. Murtiyoso ◽  
P. Grussenmeyer
Keyword(s):  
Ground Truth ◽  
Point Clouds ◽  
Zoological Museum ◽  
Registration Method ◽  
Difficult Time ◽  
Information Models ◽  
Building Information ◽  
Special Points ◽  
Indoor And Outdoor

<p><strong>Abstract.</strong> In the context of architectural heritage preservation, constructing building information models is an important task. However, conceiving a pertinent model is a difficult, time consuming and user-dependent task. Our laboratory has been researching methods to decrease the time and errors inferred by manual segmentation of point clouds. In the perspective of automatization of the process, we implemented an automated registration method that used only keypoints. Keypoints are special points that hold more information about the global structure of the cloud. In order to detect keypoints, we used the Point Cloud Library (PCL) toolbox. The pertinence of the method was evaluated by registering more than 300 clouds of the zoological museum of Strasbourg. The quality of the keypoint detection was first verified on geo-referenced indoor point clouds. Then we applied this method to register the indoor and outdoor point clouds that have much less area in common; those common points being generally the doors and windows of the façade. The registrations of indoor point clouds were satisfying, with mean distances to the ground truth inferior to 20&amp;thinsp;cm. While the first result for joint indoor/outdoor registration are promising, it may be improved in future works.</p>

scholarly journals AUTOMATING THE VERIFICATION OF HERITAGE BUILDING INFORMATION MODELS CREATED FROM POINT CLOUD DATA

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 455-460 ◽  
Author(s):  
H. Macher ◽  
L. Chow ◽  
S. Fai
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Cloud Data ◽  
Remote Sensors ◽  
Information Models ◽  
Building Information ◽  
Heritage Buildings ◽  
Heritage Building ◽  
Verification Process ◽  
Metric Information

<p><strong>Abstract.</strong> The use of remote sensors to acquire metric information for building information modelling (BIM) of heritage buildings is now common. Problematically, the creation of models from that information is still largely a manual and non-quantifiable process. As a result, a key aspect of the scan-to-BIM process is verification of the accuracy of the model in relation to the metric information. The most common method to check a model element constructed from a point cloud seems to be the analysis of deviations between this element and the corresponding point cloud (Anil et al., 2013; Tang et al., 2011). It is comprised of three main steps: the computation, the visualisation and the analysis of deviations. The verification process is particularly onerous for large-scale buildings where it is necessary to ensure that all elements of a model are consistent with metric data that may come from diverse sources (Chow and Fai, 2017). In this paper, we discuss the development of a plug-in for Autodesk Revit that automates this verification process.</p>

scholarly journals Optimum Assembly Planning for Modular Construction Using BIM and 3D Point Clouds

2016 ◽  
Author(s):  
Mohammad Nahangi ◽  
Christopher Rausch ◽  
Carl Haas
Keyword(s):  
Point Cloud ◽  
Cloud Model ◽  
Point Clouds ◽  
Assembly Planning ◽  
Modular Construction ◽  
Optimization Framework ◽  
3D Point Clouds ◽  
Information Models ◽  
Building Information ◽  
Point Cloud Model

Geometric and dimensional deviations often create challenges for component aggregation in the assembly of interchangeable components in modular construction. Although the components are designed interchangeably, once they are fabricated, there are inevitable discrepancies between the designed and built states. Such discrepancies create problems for fitting interchangeable modular components. This paper presents a framework for optimally planning the assembly of interchangeable components based on their as-built state. A 3D point cloud model is captured and the critical interfaces between modules are compared to the original state, integrated in the building information models (BIM), as 3D drawings. The optimization framework is implemented based on two different approaches: (1) minimization of the total deviation for minimizing rework, and (2) intervention of rework by finding the best matching component for each investigated slot. Results show that the method can be effectively used for reducing rework in modular construction by optimum assembly planning.

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).

scholarly journals COMBINATION OF THERMAL AND GEOMETRIC INFORMATION FOR BIM ENRICHMENT

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 719-725 ◽  
Author(s):  
H. Macher ◽  
M. Boudhaim ◽  
P. Grussenmeyer ◽  
M. Siroux ◽  
T. Landes
Keyword(s):  
Laser Scanning ◽  
Thermal Analyses ◽  
Laser Scanner ◽  
Point Clouds ◽  
Existing Buildings ◽  
Energy Audit ◽  
Geometric Information ◽  
Information Models ◽  
Building Information ◽  
Reduction Of Energy Consumption

<p><strong>Abstract.</strong> In the context of building renovation, infrared (IR) cameras are widely used to perform the energy audit of buildings. They allow analysing precisely the energetic performances of existing buildings and thermal analyses represent a key step for the reduction of energy consumption. They are also used to assess the thermal comfort of people living or working in a building. Building Information Models (BIM) are widespread to plan the rehabilitation of existing buildings and laser scanning is now commonly used to capture the geometry of buildings for as-built BIM creation. The combination of thermographic and geometric data presents a high number and variety of applications (Lagüela and Díaz-Vilariño, 2016). However, geometric and thermal information are generally acquired separately by different building stakeholders and thermal analyses are performed with independence of geometry. In this paper, the combination of thermal and geometric information is investigated for indoor of buildings. The aim of the project is to create 3D thermographic point clouds based on data acquired by a laser scanner and a thermal camera. Based on these point clouds, BIM models might be enriched with thermal information through the scan-to-BIM process.</p>

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