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.
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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
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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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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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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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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11 May 2004
TL;DR: Two new regional shape descriptors are introduced: 3D shape contexts and harmonic shape contexts that outperform the others on cluttered scenes on recognition of vehicles in range scans of scenes using a database of 56 cars.
Abstract: Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizing vehicles in range scans of scenes using a database of 56 cars. We compare the two novel descriptors to an existing descriptor, the spin image, showing that the shape context based descriptors have a higher recognition rate on noisy scenes and that 3D shape contexts outperform the others on cluttered scenes.
919 citations
24 Jul 1994
TL;DR: A key ingredient in the method, and a principal contribution of this paper, is the introduction of a new class of piecewise smooth surface representations based on subdivision that can be fit to scattered range data using an unconstrained optimization procedure.
Abstract: We present a general method for automatic reconstruction of accurate, concise, piecewise smooth surface models from scattered range data. The method can be used in a variety of applications such as reverse engineering—the automatic generation of CAD models from physical objects. Novel aspects of the method are its ability to model surfaces of arbitrary topological type and to recover sharp features such as creases and corners. The method has proven to be effective, as demonstrated by a number of examples using both simulated and real data.A key ingredient in the method, and a principal contribution of this paper, is the introduction of a new class of piecewise smooth surface representations based on subdivision. These surfaces have a number of properties that make them ideal for use in surface reconstruction: they are simple to implement, they can model sharp features concisely, and they can be fit to scattered range data using an unconstrained optimization procedure.
806 citations
TL;DR: A new form of point representation for describing 3D free-form surfaces is proposed, which serves to describe the structural neighbourhood of a point in a more complete manner than just using the 3D coordinates of the point.
Abstract: Few systems capable of recognizing complex objects with free-form (sculptured) surfaces have been developed. The apparent lack of success is mainly due to the lack of a competent modelling scheme for representing such complex objects. In this paper, a new form of point representation for describing 3D free-form surfaces is proposed. This representation, which we call the point signature, serves to describe the structural neighbourhood of a point in a more complete manner than just using the 3D coordinates of the point. Being invariant to rotation and translation, the point signature can be used directly to hypothesize the correspondence to model points with similar signatures. Recognition is achieved by matching the signatures of data points representing the sensed surface to the signatures of data points representing the model surface.
The use of point signatures is not restricted to the recognition of a single-object scene to a small library of models. Instead, it can be extended naturally to the recognition of scenes containing multiple partially-overlapping objects (which may also be juxtaposed with each other) against a large model library. No preliminary phase of segmenting the scene into the component objects is required. In searching for the appropriate candidate model, recognition need not proceed in a linear order which can become prohibitive for a large model library. For a given scene, signatures are extracted at arbitrarily spaced seed points. Each of these signatures is used to vote for models that contain points having similar signatures. Inappropriate models with low votes can be rejected while the remaining candidate models are ordered according to the votes they received. In this way, efficient verification of the hypothesized candidates can proceed by testing the most likely model first. Experiments using real data obtained from a range finder have shown fast recognition from a library of fifteen models whose complexities vary from that of simple piecewise quadric shapes to complicated face masks. Results from the recognition of both single-object and multiple-object scenes are presented.
653 citations
"Automatic reconstruction of as-buil..." refers background in this paper
...Other descriptors include point signatures [17], Euclidean 3D grid histograms [64], 3D shape contexts [28], and bitangent curves [98]....
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01 Jan 1986-Graphical Models \/graphical Models and Image Processing \/computer Vision, Graphics, and Image Processing
TL;DR: Experimental results for real and synthetic range images show the properties, usefulness, and importance of differential-geometric surface characteristics.
Abstract: In recent years there has been a tremendous increase in computer vision research using range images (or depth maps) as sensor input data. The most attractive feature of range images is the explicitness of the surface information. Many industrial and navigational robotic tasks will be more easily accomplished if such explicit depth information can be efficiently obtained and interpreted. Intensity image understanding research has shown that the early processing of sensor data should be data-driven. The goal of early processing is to generate a rich description for later processing. Classical differential geometry provides a complete local description of smooth surfaces. The first and second fundamental forms of surfaces provide a set of differential-geometric shape descriptors that capture domain-independent surface information. Mean curvature and Gaussian curvature are the fundamental second-order surface characteristics that possess desirable invariance properties and represent extrinsic and intrinsic surface geometry respectively. The signs of these surface curvatures are used to classify range image regions into one of eight basic viewpoint-independent surface types. Experimental results for real and synthetic range images show the properties, usefulness, and importance of differential-geometric surface characteristics.
599 citations
"Automatic reconstruction of as-buil..." refers background or methods in this paper
...Furthermore, existing research studies that do involve performance evaluation of related techniques lie mainly within the computer vision and remote sensing domains [8,63], and the performance measures used in those studies do not directly address the requirements of the AECdomain....
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...Inspired by performancemeasures previously proposed for geometric modeling and object recognition algorithms [8,63], we now identify a set of performance measures for modeling as-built BIMs and relate them to the information requirements of the AEC domain (GSA 2007)....
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01 Jul 2005
TL;DR: A robust moving least-squares technique for reconstructing a piecewise smooth surface from a potentially noisy point cloud is introduced, based on a new robust statistics method for outlier detection: the forward-search paradigm.
Abstract: We introduce a robust moving least-squares technique for reconstructing a piecewise smooth surface from a potentially noisy point cloud. We use techniques from robust statistics to guide the creation of the neighborhoods used by the moving least squares (MLS) computation. This leads to a conceptually simple approach that provides a unified framework for not only dealing with noise, but also for enabling the modeling of surfaces with sharp features.Our technique is based on a new robust statistics method for outlier detection: the forward-search paradigm. Using this powerful technique, we locally classify regions of a point-set to multiple outlier-free smooth regions. This classification allows us to project points on a locally smooth region rather than a surface that is smooth everywhere, thus defining a piecewise smooth surface and increasing the numerical stability of the projection operator. Furthermore, by treating the points across the discontinuities as outliers, we are able to define sharp features. One of the nice features of our approach is that it automatically disregards outliers during the surface-fitting phase.
584 citations
"Automatic reconstruction of as-buil..." refers background in this paper
...Computing surface normals can be challenging near boundaries, where the underlying surface is discontinuous or changes orientation, because data from other surfaces can bias the estimate [27]....
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