☆ 4.6 Review

Construction and Maintenance of Building Geometric Digital Twins: State of the Art Review

SENSORS (2023)

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Article Construction & Building Technology

Point Cloud Information Modeling: Deep Learning Based Automated Information Modeling Framework for Point Cloud Data

Jisoo Park et al.

Summary: This study proposes a novel information modeling framework for point clouds, called PCIM, which can automatically recognize construction objects and store information in the original point cloud data with a hierarchical structure. It addresses the limitations of the conventional Scan-to-BIM pipeline and provides an effective tool for as-is information modeling during construction.

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2022)

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Article Construction & Building Technology

Enriching geometric digital twins of buildings with small objects by fusing laser scanning and AI-based image recognition

Yuandong Pan et al.

Summary: This paper introduces a novel method to enrich geometric digital twins of buildings by capturing important entities from the electrical and fire-safety domain. The method fuses laser scanning and photogrammetry to capture relevant objects, recognize them in 2D images, and map them to a 3D space. The resulting digital twin contains geometric information, semantic information, and useful text information, and can be used for condition monitoring, facility maintenance, and management.

AUTOMATION IN CONSTRUCTION (2022)

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Proceedings Paper Computer Science, Artificial Intelligence

SoftGroup for 3D Instance Segmentation on Point Clouds

Thang Vu et al.

Summary: This paper proposes a 3D instance segmentation method called SoftGroup, which addresses the problems of existing methods through soft grouping and refinement. Experimental results demonstrate its efficacy and its performance surpasses prior methods.

2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022) (2022)

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Proceedings Paper Geography, Physical

LINKED BUILDING DATA FOR CONSTRUCTION SITE MONITORING: A TEST CASE

M. Bassier et al.

Summary: This paper presents a tentative framework for Linked Data usage on construction sites, combining various observations to establish a comprehensive analysis of the site.

XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION II (2022)

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Article Construction & Building Technology

An efficient data structure approach for BIM-to-point-cloud change detection using modifiable nested octree

Sangyoon Park et al.

Summary: This study introduces a high-performance algorithm for detecting discrepancies between as-planned BIM and as-is point cloud, using a data structure approach based on modifiable nested octree indexing. Experimental results showed significant improvement in computation performance, with time complexity represented as O(logN) as the number of meshes in BIM geometry increased.

AUTOMATION IN CONSTRUCTION (2021)

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Review Chemistry, Multidisciplinary

Literature Review of Digital Twins Applications in Construction Workforce Safety

Lei Hou et al.

Summary: For many decades, the construction sector has faced safety challenges, despite efforts to improve overall safety. The concept of digital twins has the potential to enhance construction health and safety, but the industry has yet to fully exploit these innovative technologies.

APPLIED SCIENCES-BASEL (2021)

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Review Computer Science, Interdisciplinary Applications

Digital Twins: Review and Challenges

Maria G. Juarez et al.

Summary: This paper aims to clarify the concept, characteristics, and operation of digital twin (DT), introduce the latest trends related to this technology, and demonstrate the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING (2021)

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Article Construction & Building Technology

Automated shape and pose updating of building information model elements from 3D point clouds

Christopher Rausch et al.

Summary: This paper introduces an approach for creating geometric agency within BIMs by leveraging their parametric capabilities, the accuracy of 3D point clouds, and the dexterity of metaheuristics, resulting in a dynamic BIM capable of updating its geometry to match a 3D point cloud. A case study demonstrates a significant reduction in average error between a BIM and the as-built conditions, providing a way to progressively capture accurate as-built conditions in BIM and predict potential assembly conflicts.

AUTOMATION IN CONSTRUCTION (2021)

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Article Construction & Building Technology

Fully automated generation of parametric BIM for MEP scenes based on terrestrial laser scanning data

Boyu Wang et al.

Summary: This study introduces a fully automated approach to converting terrestrial laser scanning data to well-connected as-built BIMs for MEP scenes. By dividing MEP components into regular and irregular shapes, a 2D to 3D analysis framework is developed to detect objects and extract accurate geometry information.

AUTOMATION IN CONSTRUCTION (2021)

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Article Chemistry, Multidisciplinary

Wall Structure Geometry Verification Using TLS Data and BIM Model

Gabriela Bariczova et al.

Summary: Building information modeling (BIM) is a significant advancement in digitizing and informatizing the construction process, where the virtual model serves as a source for geometry verification of building structures. Terrestrial laser scanning (TLS) and close-range photogrammetry are effective methods for spatial data collection. The comparison between as-built models and BIM model enables assessment of building quality.

APPLIED SCIENCES-BASEL (2021)

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Article Geochemistry & Geophysics

Building Change Detection for Remote Sensing Images Using a Dual-Task Constrained Deep Siamese Convolutional Network Model

Yi Liu et al.

Summary: The proposed dual-task constrained deep Siamese convolutional network (DTCDSCN) model achieves both change detection and semantic segmentation simultaneously, improving feature extraction and representation to address the issue of lack of discriminative features in change detection. Experimental results demonstrate state-of-the-art performance on the WHU building data set, showcasing the effectiveness of the proposed method.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2021)

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Article Geography, Physical

Floorplan generation from 3D point clouds: A space partitioning approach

Hao Fang et al.

Summary: The novel approach presented in this paper automatically reconstructs the floorplan of indoor environments by decomposing the space into a polygonal partition and selecting edges belonging to wall structures through energy minimization. It demonstrates high robustness to imperfect data and competitive performance in terms of geometric accuracy and output simplicity compared to existing methods.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

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Article Computer Science, Interdisciplinary Applications

CorDet: Corner-Aware 3D Object Detection Networks for Automated Scan-to-BIM

Yongzhi Xu et al.

Summary: This study explores an automatic, high-precision scan-to-BIM method using a new 3D object detection network called CorDet, which can accurately reconstruct building objects by simultaneously learning object-level and corner-level features through deep learning techniques.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2021)

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Article Geography, Physical

Vectorized indoor surface reconstruction from 3D point cloud with multistep 2D optimization

Jiali Han et al.

Summary: An effective multi-step pipeline is proposed in this paper for reconstructing vectorized models from indoor point clouds without assumptions about the Manhattan or Atlanta world. Experimental results demonstrate that the proposed method can achieve accurate and compact vectorized models on both precise LiDAR data and defect-laden MVS data compared to other state-of-the-art approaches.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

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Article Construction & Building Technology

Three-Dimensional Object Detection with Deep Neural Networks for Automatic As-Built Reconstruction

Yongzhi Xu et al.

Summary: This study aims to develop an end-to-end, fully automatic, and object-level reconstruction approach to converting point clouds of non-Manhattan and multiroom buildings into 3D models. By using a two-stage 3D object-detection method with region-based convolutional neural networks (R-CNN) and feature fusion between sparse 3D and two-dimensional bird's eye view (BEV) feature maps, the generality and efficiency of modeling building primitives have been improved.

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2021)

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Review Multidisciplinary Sciences

Industrial applications of digital twins

Yuchen Jiang et al.

Summary: A digital twin is a virtual replica continuously updated with data from its physical counterpart, serving as the pillar of Industry 4.0 and the foundation of future innovation. This article focuses on the use of digital twins in smart manufacturing, emphasizing plantwide optimization. The main capabilities of digital twins (mirroring, shadowing, threading) are discussed, with a perspective on the future provided.

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

Zhihao Liang et al.

Summary: In this study, we propose an end-to-end solution called Semantic Superpoint Tree Network (SSTNet) to address the challenge of 3D scene instance segmentation. SSTNet utilizes a semantic superpoint tree (SST) to extract object instances and includes a CliqueNet module to optimize the accuracy of instance extraction. Experimental results demonstrate the effectiveness of this method.

2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

Hierarchical Aggregation for 3D Instance Segmentation

Shaoyu Chen et al.

Summary: This work introduces a fast instance segmentation framework named HAIS, utilizing clustering and hierarchical aggregation methods, achieving the highest performance on the ScanNet v2 benchmark.

2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021) (2021)

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Article Computer Science, Interdisciplinary Applications

Vision-based automated bridge component recognition with high-level scene consistency

Yasutaka Narazaki et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2020)

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Article Construction & Building Technology

Geometric quality inspection of prefabricated MEP modules with 3D laser scanning

Jingjing Guo et al.

AUTOMATION IN CONSTRUCTION (2020)

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Article Construction & Building Technology

Semantic segmentation of point clouds of building interiors with deep learning: Augmenting training datasets with synthetic BIM-based point clouds

Jong Won et al.

AUTOMATION IN CONSTRUCTION (2020)

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Article Environmental Sciences

3D Point Cloud and BIM-Based Reconstruction for Evaluation of Project by As-Planned and As-Built

Seungho Kim et al.

REMOTE SENSING (2020)

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Article Computer Science, Artificial Intelligence

Automated segmentation of RGB-D images into a comprehensive set of building components using deep learning

Thomas Czerniawski et al.

ADVANCED ENGINEERING INFORMATICS (2020)

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Article Computer Science, Software Engineering

State-of-the-art in Automatic 3D Reconstruction of Structured Indoor Environments

Giovanni Pintore et al.

COMPUTER GRAPHICS FORUM (2020)

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Article Engineering, Multidisciplinary

Automated region-of-interest localization and classification for vision-based visual assessment of civil infrastructure

Chul Min Yeum et al.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2019)

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Article Geography, Physical

Automatic reconstruction of fully volumetric 3D building models from oriented point clouds

Sebastian Ochmann et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2019)

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Article Computer Science, Interdisciplinary Applications

Deep Learning Approach to Point Cloud Scene Understanding for Automated Scan to 3D Reconstruction

Jingdao Chen et al.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2019)

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Article Computer Science, Interdisciplinary Applications

Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization

Xiao Liang

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)

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Article Computer Science, Interdisciplinary Applications

Shape Grammar Approach to 3D Modeling of Indoor Environments Using Point Clouds

H. Tran et al.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2019)

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Article Computer Science, Information Systems

Semantic Geometric Modelling of Unstructured Indoor Point Cloud

Wenzhong Shi et al.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2019)

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Article Construction & Building Technology

Comparison of point cloud data and 3D CAD data for on-site dimensional inspection of industrial plant piping systems

Cong Hong Phong Nguyen et al.

AUTOMATION IN CONSTRUCTION (2018)

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Article Construction & Building Technology

Door detection in 3D coloured point clouds of indoor environments

B. Quintana et al.

AUTOMATION IN CONSTRUCTION (2018)

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Article Computer Science, Artificial Intelligence

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Liang-Chieh Chen et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)

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Article Computer Science, Information Systems

Hybrid approach for alignment of a pre-processed three-dimensional point cloud, video, and CAD model using partial point cloud in retrofitting applications

Ashok Kumar Patil et al.

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS (2018)

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Article Construction & Building Technology

Prioritizing object types for modelling existing industrial facilities

Eva Agapaki et al.

AUTOMATION IN CONSTRUCTION (2018)

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Article Chemistry, Multidisciplinary

From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings

Helene Macher et al.

APPLIED SCIENCES-BASEL (2017)

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Article Robotics

Automatic Room Segmentation From Unstructured 3-D Data of Indoor Environments

Rares Ambrus et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2017)

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Article Computer Science, Hardware & Architecture

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky et al.

COMMUNICATIONS OF THE ACM (2017)

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Proceedings Paper Computer Science, Artificial Intelligence

ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes

Angela Dai et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

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Proceedings Paper Computer Science, Artificial Intelligence

Matterport3D: Learning from RGB-D Data in Indoor Environments

Angel Chang et al.

PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON 3D VISION (3DV) (2017)

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Article Construction & Building Technology

Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM

Min-Koo Kim et al.

AUTOMATION IN CONSTRUCTION (2016)

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Article Computer Science, Interdisciplinary Applications

Non-Uniform B-Spline Surface Fitting from Unordered 3D Point Clouds for As-Built Modeling

Andrey Dimitrov et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2016)

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Article Computer Science, Interdisciplinary Applications

Evaluation of Different Features for Matching Point Clouds to Building Information Models

Te Gao et al.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2016)

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Article Computer Science, Artificial Intelligence

An approach to combine progressively captured point clouds for BIM update

Te Gao et al.

ADVANCED ENGINEERING INFORMATICS (2015)

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Article Computer Science, Artificial Intelligence

State of research in automatic as-built modelling

Viorica Patraucean et al.

ADVANCED ENGINEERING INFORMATICS (2015)

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Article Construction & Building Technology

Segmentation of building point cloud models including detailed architectural/structural features and MEP systems

Andrey Dimitrov et al.

AUTOMATION IN CONSTRUCTION (2015)

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Article Construction & Building Technology

A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning

Min-Koo Kim et al.

AUTOMATION IN CONSTRUCTION (2015)

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Article Construction & Building Technology

The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components

Frederic Bosche et al.

AUTOMATION IN CONSTRUCTION (2015)

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Proceedings Paper Computer Science, Artificial Intelligence

Fast R-CNN

Ross Girshick

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)

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Article Computer Science, Interdisciplinary Applications

Automatic Detection of Cylindrical Objects in Built Facilities

Mahmoud Fouad Ahmed et al.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2014)

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Article Computer Science, Interdisciplinary Applications

Tracking the Built Status of MEP Works: Assessing the Value of a Scan-vs.-BIM System

Frederic Bosche et al.

JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2014)

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Article Construction & Building Technology

Automated progress control using laser scanning technology

Chengyi Zhang et al.

AUTOMATION IN CONSTRUCTION (2013)

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Article Construction & Building Technology

Automated construction progress measurement using a 4D building information model and 3D data

Changmin Kim et al.

AUTOMATION IN CONSTRUCTION (2013)

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Article Construction & Building Technology

Toward Automated Earned Value Tracking Using 3D Imaging Tools

Yelda Turkan et al.

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT (2013)

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Article Construction & Building Technology

Automated progress tracking using 4D schedule and 3D sensing technologies

Yelda Turkan et al.

AUTOMATION IN CONSTRUCTION (2012)

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Article Construction & Building Technology

Automated retrieval of 3D CAD model objects in construction range images

F. Bosche et al.

AUTOMATION IN CONSTRUCTION (2008)

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Article Robotics

Natural terrain classification using three-dimensional ladar data for ground robot mobility

Jean-Francois Lalonde et al.

JOURNAL OF FIELD ROBOTICS (2006)

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