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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06 Mar 2018
TL;DR: The results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed.
Abstract: In this article the analysis of gaps in processing of raw laser scanning data and results of bridging the gaps discovered on the base of usage of laser scanning data for historic building information modeling is presented. The results of the development of a unified hybrid technology for the processing, storage, access and visualization of combined laser scanning and photography data about historical buildings are analyzed. The first result of the technology application for the historical building of St. Petersburg Polytechnic University shows reliability of the proposed approaches.
13 citations
01 Jan 2019
TL;DR: Through the proposed approach, experts can develop highly accurate FE meshes to assess the stability of the structure up to as-built conditions and taking into account existing damage patterns.
Abstract: The structural analysis of buildings requires accurate spatial models. Additionally, spatial information on pathologies such as settlement-induced damage is paramount in the assessment of heritage assets. This spatial information is used as a basis for Finite Element Methods (FEM) to evaluate the stability of the structure. Traditional data acquisition approaches rely on manual measurements which are labor intensive and error prone. Therefore, major simplifications are made to document structures efficiently. The goal of this research is to provide faster and more accurate procedures to capture the spatial information required by a Finite Element (FE) mesh. This paper presents a semi-automated approach to create accurate models of complex heritage buildings for the purpose of structural analysis. By employing remote sensing techniques such as terrestrial laser scanning and photogrammetry, a complex mesh of the structure is created. Also, a methodology is proposed to capture crack information. A stepwise approach is elaborated to illustrate how the spatial information is adapted towards a FE mesh. The results show a significant difference between the geometry of our model and a traditional wire-frame model. Not only does accurate modelling result in deviating loads, it also affects the behavior of the object. Through the proposed approach, experts can develop highly accurate FE meshes to assess the stability of the structure up to as-built conditions and taking into account existing damage patterns.
13 citations
TL;DR: This paper proposes a layer-wise method, on the basis of 3D planar primitives, to create 2D floor plans and 3D building models that can deal with different types of point clouds and retain many structural details with respect to protruding structures, complicated ceilings, and fine corners.
Abstract: The automatic modeling of as-built building interiors, known as indoor building reconstruction, is gaining increasing attention because of its widespread applications. With the development of sensors to acquire high-quality point clouds, a new modeling scheme called scan-to-BIM (building information modeling) emerged as well. However, the traditional scan-to-BIM process is time-tedious and labor-intensive. Most existing automatic indoor building reconstruction solutions can only fit the specific data or lack of detailed model representation. In this paper, we propose a layer-wise method, on the basis of 3D planar primitives, to create 2D floor plans and 3D building models. It can deal with different types of point clouds and retain many structural details with respect to protruding structures, complicated ceilings, and fine corners. The experimental results indicate the effectiveness of the proposed method and the robustness against noises and sparse data.
13 citations
TL;DR: The proposed virtual reality-based accident causation model (VR-ACM) serves as a medium for analysis of potential underlying causes of accidents, the three-dimensional perspective of visual analysis, real-time user interactions and real- time judgement and decision-making.
Abstract: Inefficiency in real-time visualization and user interaction in traditional accident causation models (ACMs) necessitates the development of a dynamic ACM that can foster real-time hazard identification, accident prevention and interactive safety training. A virtual reality-based accident causation model (VR-ACM) may serve such a purpose. In this study, we performed a comprehensive literature review on different ACMs and safety training practices. The limitations of the existing models and practices are identified. A VR-ACM model is proposed comprising three modules: VR-based modelling and simulation, accident causation and safety training. Several research issues for VR-ACM are highlighted. An experimental study with 22 crane operators is presented, showing the applicability of the proposed model. The proposed VR-ACM serves as a medium for analysis of potential underlying causes of accidents, the three-dimensional perspective of visual analysis, real-time user interactions and real-time judgement and decision-making.
13 citations
Cites background from "Automatic reconstruction of as-buil..."
...and validating component design [113,114] Development of the DMU goes through processes such as 3D modelling for digital recreation of components, texturing for realistic scene creation [115,116] and creation of a 3D environment for replicating the actual environment....
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TL;DR: The theory of an intelligent planning unit (IPU) is developed as a holistic approach using the smart photovoltaic system blind as one of the sustainable management strategies.
Abstract: This paper develops the theory of an intelligent planning unit (IPU) as a new thought process. The theory of an IPU is designed to (1) enable the complex built environment system to be more intelligent; (2) standardize the complex physical entities and processes at a modular scale; (3) accumulate the knowledge at different levels of complexity for IPU refinement and control; and (4) provide the decision-makers with timely and accurate information for better decision-making. An IPU can be developed by breaking down the physical entities and processes in the complex built environment system into carefully planned units (even nanoscale units). An IPU can be implemented in three phases (i.e., IPU planning, IPU application, and IPU network). This paper illustrates the theory of an IPU as a holistic approach using the smart photovoltaic system blind as one of the sustainable management strategies. The IPU case scenario illustrates the strategy, design, replication, combination, interaction, and refineme...
13 citations
References
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TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Abstract: A new paradigm, Random Sample Consensus (RANSAC), for fitting a model to experimental data is introduced. RANSAC is capable of interpreting/smoothing data containing a significant percentage of gross errors, and is thus ideally suited for applications in automated image analysis where interpretation is based on the data provided by error-prone feature detectors. A major portion of this paper describes the application of RANSAC to the Location Determination Problem (LDP): Given an image depicting a set of landmarks with known locations, determine that point in space from which the image was obtained. In response to a RANSAC requirement, new results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form. These results provide the basis for an automatic system that can solve the LDP under difficult viewing
23,396 citations
TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Abstract: Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.
7,458 citations
"Automatic reconstruction of as-buil..." refers background in this paper
...In other fields, such as computer vision, standard test sets and performance metrics have been established [72,83], but no standard evaluation metrics have been established for as-built BIM creation as yet....
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TL;DR: Recognition-by-components (RBC) provides a principled account of the heretofore undecided relation between the classic principles of perceptual organization and pattern recognition.
Abstract: The perceptual recognition of objects is conceptualized to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components, such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed theory, recognition-by-components (RBC), is that a modest set of generalized-cone components, called geons (N £ 36), can be derived from contrasts of five readily detectable properties of edges in a two-dimensiona l image: curvature, collinearity, symmetry, parallelism, and cotermination. The detection of these properties is generally invariant over viewing position an$ image quality and consequently allows robust object perception when the image is projected from a novel viewpoint or is degraded. RBC thus provides a principled account of the heretofore undecided relation between the classic principles of perceptual organization and pattern recognition: The constraints toward regularization (Pragnanz) characterize not the complete object but the object's components. Representational power derives from an allowance of free combinations of the geons. A Principle of Componential Recovery can account for the major phenomena of object recognition: If an arrangement of two or three geons can be recovered from the input, objects can be quickly recognized even when they are occluded, novel, rotated in depth, or extensively degraded. The results from experiments on the perception of briefly presented pictures by human observers provide empirical support for the theory. Any single object can project an infinity of image configurations to the retina. The orientation of the object to the viewer can vary continuously, each giving rise to a different two-dimensional projection. The object can be occluded by other objects or texture fields, as when viewed behind foliage. The object need not be presented as a full-colored textured image but instead can be a simplified line drawing. Moreover, the object can even be missing some of its parts or be a novel exemplar of its particular category. But it is only with rare exceptions that an image fails to be rapidly and readily classified, either as an instance of a familiar object category or as an instance that cannot be so classified (itself a form of classification).
5,464 citations
"Automatic reconstruction of as-buil..." refers background in this paper
...Various researchers have proposed candidate sets of primitives, such as geons [9], superquadrics [3], and generalized cylinders [10]....
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TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.
Abstract: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems. The Face Recognition Technology (FERET) program has addressed both issues through the FERET database of facial images and the establishment of the FERET tests. To date, 14,126 images from 1,199 individuals are included in the FERET database, which is divided into development and sequestered portions of the database. In September 1996, the FERET program administered the third in a series of FERET face-recognition tests. The primary objectives of the third test were to 1) assess the state of the art, 2) identify future areas of research, and 3) measure algorithm performance.
4,816 citations
01 Aug 1996
TL;DR: This paper presents a volumetric method for integrating range images that is able to integrate a large number of range images yielding seamless, high-detail models of up to 2.6 million triangles.
Abstract: A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: incremental updating, representation of directional uncertainty, the ability to fill gaps in the reconstruction, and robustness in the presence of outliers. Prior algorithms possess subsets of these properties. In this paper, we present a volumetric method for integrating range images that possesses all of these properties. Our volumetric representation consists of a cumulative weighted signed distance function. Working with one range image at a time, we first scan-convert it to a distance function, then combine this with the data already acquired using a simple additive scheme. To achieve space efficiency, we employ a run-length encoding of the volume. To achieve time efficiency, we resample the range image to align with the voxel grid and traverse the range and voxel scanlines synchronously. We generate the final manifold by extracting an isosurface from the volumetric grid. We show that under certain assumptions, this isosurface is optimal in the least squares sense. To fill gaps in the model, we tessellate over the boundaries between regions seen to be empty and regions never observed. Using this method, we are able to integrate a large number of range images (as many as 70) yielding seamless, high-detail models of up to 2.6 million triangles.
3,282 citations
"Automatic reconstruction of as-buil..." refers background in this paper
...Non-parametric geometricmodeling reconstructs a surface, typically in the formof a triangle mesh [41], or a volume [18]....
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