scholarly journals ACCURACY INVESTIGATION ON IMAGE-BASED CHANGE DETECTION FOR BIM COMPLIANT INDOOR MODELS

Author(s):  
T. Meyer ◽  
A. Brunn ◽  
U. Stilla

Abstract. Construction progress documentation is currently of great interest for the AEC (Architecture, Engineering and Construction) branch and BIM (Building Information Modeling). Subject of this work is the geometric accuracy assessment of image-based change detection in indoor environments based on a BIM. Line features usually serve well as geodetic references in indoor scenes in order to solve for camera orientation. However, building edges are never perfectly built as planned and often geometrically generalized for BIM compliant representation. As a result, in this approach, line correspondences for image-to-model co-registration are considered as statistically uncertain entities as this is essential for dealing with metric confidences in the field of civil engineering and BIM. We present an estimation model for camera pose refinement which is based on the incidence condition between model edges and corresponding image lines. Geometric accuracies are assigned to the model edges according to the Level of Accuracy (LOA) specification for BIM. The approach is demonstrated in a series of tests using a synthetic image of an indoor BIM. The effects of varying edge detection accuracies on the estimation are investigated as well as the effects of using model edges with different geometric quality by adding Gaussian noise to the synthetic observations, each within 100 simulation runs. The results show that the camera orientation can be improved with the presented estimation model as long as the BIM compliant references meet the conditions of LOA 30 or higher (σ < 7.5 mm).

2020 ◽  
Vol 12 (15) ◽  
pp. 2492
Author(s):  
Yi Tan ◽  
Silin Li ◽  
Qian Wang

Traditional quality inspection of prefabricated components is labor intensive, time-consuming, and error prone. This study developed an automated geometric quality inspection technique for prefabricated housing units using building information modeling (BIM) and light detection and ranging (LiDAR). The proposed technique collects the 3D laser scanned data of the prefabricated unit using a LiDAR which contains accurate as-built surface geometries of the prefabricated unit. On the other hand, the BIM model of the prefabricated unit contains the as-designed geometries of the unit. The scanned data and BIM model are then automatically processed to inspect the geometric quality of individual elements of the prefabricated units including both structural and mechanical elements, as well as electrical and plumbing (MEP) elements. To validate the proposed technique, experiments were conducted on two prefabricated bathroom units (PBUs). The inspection results showed that the proposed technique can provide accurate quality inspection results with 0.7 mm and 0.9 mm accuracy for structural and MEP elements, respectively. In addition, the experiments also showed that the proposed technique greatly improves the inspection efficiency regarding time and labor.


2020 ◽  
Vol 10 (8) ◽  
pp. 2817 ◽  
Author(s):  
Uuganbayar Gankhuyag ◽  
Ji-Hyeong Han

In the architecture, engineering, and construction (AEC) industry, creating an indoor model of existing buildings has been a challenging task since the introduction of building information modeling (BIM). Because the process of BIM is primarily manual and implies a high possibility of error, the automated creation of indoor models remains an ongoing research. In this paper, we propose a fully automated method to generate 2D floorplan computer-aided designs (CADs) from 3D point clouds. The proposed method consists of two main parts. The first is to detect planes in buildings, such as walls, floors, and ceilings, from unstructured 3D point clouds and to classify them based on the Manhattan-World (MW) assumption. The second is to generate 3D BIM in the industry foundation classes (IFC) format and a 2D floorplan CAD using the proposed line-detection algorithm. We experimented the proposed method on 3D point cloud data from a university building, residential houses, and apartments and evaluated the geometric quality of a wall reconstruction. We also offer the source code for the proposed method on GitHub.


Author(s):  
F. Capocchiano ◽  
R. Ravanelli ◽  
M. Crespi

Within the construction sector, Building Information Models (BIMs) are more and more used thanks to the several benefits that they offer in the design of new buildings and the management of the existing ones. Frequently, however, BIMs are not available for already built constructions, but, at the same time, the range camera technology provides nowadays a cheap, intuitive and effective tool for automatically collecting the 3D geometry of indoor environments. It is thus essential to find new strategies, able to perform the first step of the scan to BIM process, by extracting the geometrical information contained in the 3D models that are so easily collected through the range cameras.<br><br> In this work, a new algorithm to extract planimetries from the 3D models of rooms acquired by means of a range camera is therefore presented. The algorithm was tested on two rooms, characterized by different shapes and dimensions, whose 3D models were captured with the Occipital Structure Sensor<sup>TM</sup>. The preliminary results are promising: the developed algorithm is able to model effectively the 2D shape of the investigated rooms, with an accuracy level comprised in the range of 5 - 10 cm. It can be potentially used by non-expert users in the first step of the BIM generation, when the building geometry is reconstructed, for collecting crowdsourced indoor information in the frame of BIMs Volunteered Geographic Information (VGI) generation.


Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3944 ◽  
Author(s):  
Martin Velas ◽  
Michal Spanel ◽  
Tomas Sleziak ◽  
Jiri Habrovec ◽  
Adam Herout

This paper presents a human-carried mapping backpack based on a pair of Velodyne LiDAR scanners. Our system is a universal solution for both large scale outdoor and smaller indoor environments. It benefits from a combination of two LiDAR scanners, which makes the odometry estimation more precise. The scanners are mounted under different angles, thus a larger space around the backpack is scanned. By fusion with GNSS/INS sub-system, the mapping of featureless environments and the georeferencing of resulting point cloud is possible. By deploying SoA methods for registration and the loop closure optimization, it provides sufficient precision for many applications in BIM (Building Information Modeling), inventory check, construction planning, etc. In our indoor experiments, we evaluated our proposed backpack against ZEB-1 solution, using FARO terrestrial scanner as the reference, yielding similar results in terms of precision, while our system provides higher data density, laser intensity readings, and scalability for large environments.


2018 ◽  
Vol 7 (8) ◽  
pp. 321 ◽  
Author(s):  
Yueyong Pang ◽  
Chi Zhang ◽  
Liangchen Zhou ◽  
Bingxian Lin ◽  
Guonian Lv

Indoor space information extraction is an important aspect of reconstruction for building information modeling and a necessary process for geographic information system from outdoor to indoor. Entity model extracting methods provide advantages in terms of accuracy for building indoor spaces, as compared with network and grid model methods, and the extraction results can be converted into a network or grid model. However, existing entity model extracting methods based on a search loop do not consider the complex indoor environment of a building, such as isolated columns and walls or cross-floor spaces. In this study, such complex indoor environments are analyzed in detail, and a new approach for extracting buildings’ indoor space information is proposed. This approach is based on indoor space boundary calculation, the Boolean difference for single-floor space extraction, relationship reconstruction, and cross-floor space extraction. The experimental results showed that the proposed method can accurately extract indoor space information from the complex indoor environment of a building with geometric, semantic, and relationship information. This study is theoretically important for better understanding the complexity of indoor space extraction and practically important for improving the modeling accuracy of buildings.


The variants of the division of the life cycle of a construction object at the stages adopted in the territory of the Russian Federation, as well as in other countries are considered. Particular attention is paid to the exemplary work plan – "RIBA plan of work", used in England. A feature of this document is its applicability in the information modeling of construction projects (Building information Modeling – BIM). The article presents a structural and logical scheme of the life cycle of a building object and a list of works that are performed using information modeling technology at various stages of the life cycle of the building. The place of information models in the process of determining the service life of the building is shown. On the basis of the considered sources of information, promising directions for the development of the life cycle management system of the construction object (Life Cycle Management) and the development of the regulatory framework in order to improve the use of information modeling in construction are given.


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