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: A novel derivative-free optimization (DFO)-based approach for effective ASD is developed by transforming ASD into a nonlinear optimization problem involving architectural regularity and topology, and an in-house ODAS (Optimization-based Detection of Architectural Symmetries) approach is developed to solve the formulated problem using a set of state-of-the-art DFO algorithms.
Abstract: Symmetry is ubiquitous in architecture, across both time and place. Automated architectural symmetry detection (ASD) from a data source is not only an intriguing inquiry in its own right, but also a step towards creation of semantically rich building and city information models with applications in architectural design, construction management, heritage conservation, and smart city development. While recent advances in sensing technologies provide inexpensive yet high-quality architectural 3D point clouds, existing methods of ASD from these data sources suffer several weaknesses including noise sensitivity, inaccuracy, and high computational loads. This paper aims to develop a novel derivative-free optimization (DFO)-based approach for effective ASD. It does so by firstly transforming ASD into a nonlinear optimization problem involving architectural regularity and topology. An in-house ODAS (Optimization-based Detection of Architectural Symmetries) approach is then developed to solve the formulated problem using a set of state-of-the-art DFO algorithms. Efficiency, accuracy, and robustness of ODAS are gauged from the experimental results on nine sets of real-life architectural 3D point clouds, with the computational time for ASD from 1.4 million points only 3.7 s and increasing in a sheer logarithmic order against the number of points. The contributions of this paper are threefold. Firstly, formulating ASD as a nonlinear optimization problem constitutes a methodological innovation. Secondly, the provision of up-to-date, open source DFO algorithms allows benchmarking in the future development of free, fast, accurate, and robust approaches for ASD. Thirdly, the ODAS approach can be directly used to develop building and city information models for various value-added applications.
21 citations
TL;DR: This research studies the application of Brodu and Lague's morphological segmentation algorithm called CANUPO to classify the architectural components of the facade of the 16th-century Casa de Pilatos Palace in Seville, Spain from a Terrestrial Laser Scanning (TLS) point cloud dataset.
21 citations
TL;DR: Close range photogrammetry appears to be the most appropriate method for damage detection of forest roads due to the time needed and the accuracy of the road wearing course damage detected by four different remote sensing methods.
Abstract: Currently, a large part of forest roads with a bituminous surface course constructed in the Czech Republic in the second half of the last century has been worn out. The aim of the study is to verify the possibility and the accuracy of the road wearing course damage detected by four different remote sensing methods: close range photogrammetry, terrestrial laser scanning, mobile laser scanning and airborne laser scanning. At the beginning of verification, cross sections of the road surface were surveyed geodetically and then compared with the cross sections created in the DTMs which were acquired using the four methods mentioned above. The differences calculated between particular models and geodetic measurements show that close range photogrammetry achieved an RMSE of 0.0110 m and the RMSE of terrestrial laser scanning was 0.0243 m. Based on these results, we can conclude that these two methods are sufficient for the monitoring of the asphalt wearing course of forest roads. These methods allow precise and objective localization, size and quantification of the road damage. By contrast, mobile laser scanning with an RMSE of 0.3167 m does not reach the required precision for the damage detection of forest roads due to the vegetation that affects the precision of the measurements. Similar results are achieved by airborne laser scanning, with an RMSE of 0.1392 m. As regards the time needed, close range photogrammetry appears to be the most appropriate method for damage detection of forest roads.
21 citations
TL;DR: The proposed approach combines parametric and reality-based modelling approaches and takes advantage of the strengths of each, thus meeting the requirements of a variety of applications, and it simplifies the scan-to-BIM process which has been recognised as a bottleneck in heritage BIM.
21 citations
13 May 2014
TL;DR: In this paper, a framework for rapid as-built modeling using 3D point cloud data captured by a handheld lidar is presented, which involves five key stages from data capturing to create a final model.
Abstract: The need for development of reliable and efficient real-time data acquisition systems has recently attracted a great deal of attention in the construction industry, basically due to the demands for highly frequent updates in most visualization, optimization and coordination-related applications. The predominant data that has been used in the construction industry so far is rather less accurate. Moreover, the conventional methods of data acquisition are based on fieldwork that is timeconsuming, expensive and labour-intensive. Accuracy of original data and efficiency of data acquisition could be enhanced using new lidar technologies. Lidar is the advanced remote sensing technology that is able to provide 3D data with centimetre to millimetre level accuracy effectively and efficiently. However, the implementation of 3D data for accurate as-built creation is still challenging especially for openings and fine details of the construction objects in an indoor environment. This paper presents a framework for rapid as-built modelling using 3D point cloud data captured by a handheld lidar. The procedure involves five key stages from data capturing to create a final model. This paper reports the implementation of the framework using the state-of-the-art mobile lidar to analyse fine details of a sample building. Lidar data of a sample building in an indoor environment is captured using a mobile laser scanner and is analysed after registration and segmentation processes. The reconstructed model using the as-built data is compared with the existing 2D AutoCAD plans of the sample building and the traditional measurements in order to verify the accuracy of the proposed method. The results of this on-going study confirm that the proposed model development technique can serve as a reliable tool for accurate development of rapid as-built building models (rABM). The accuracy ranges from 5 to 30 mm, depending on the object size and position. The proposed algorithm was shown to be highly efficient in identifying the main visible components in the buildings. INTRODUCTION New technologies such as 3D laser scanners and building information modelling (BIM) offer great possibilities in the construction engineering area (Love et al. 2014; Porwal and Hewage 2013; Volk et al. 2014). Since the new technologies 209 Construction Research Congress 2014 ©ASCE 2014
21 citations
Cites background from "Automatic reconstruction of as-buil..."
...While many studies were attempted to provide a solution to collect and record the completed construction objects for an as-built purpose, the effort to automate the process of an as-built creation on time is still in the early stages (Tang et al. 2010)....
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...(c) Details of Study Extent: According to Tang et al. (2010), the majority of existing work focuses on the simplest elements of a building rather than details in their geometry where those elements are not yet captured....
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...According to (Tang et al. 2010), the majority T1=77....
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...A considerable amount of research provided techniques to address the problem of recognition of interior and exterior objects in construction (Tang et al. 2010; Volk et al. 2014)....
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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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