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.
Citations
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10 Jun 2018
TL;DR: In an effort to leverage the success of deep learning for Scan-to-BIM, 3DFacilities, an annotated dataset of 3D reconstructions of building facilities is presented, containing over 11,000 individual RGB-D frames comprising 50 scene reconstructions annotated with 3D camera poses and per-vertex andper-pixel annotations.
Abstract: Scan-to-BIM is the process of converting 3D reconstructions into building information models (BIM). Currently, it involves manual tracing of point clouds by human users in BIM authoring tools, with some automation functionality available for walls, floors, windows, doors, and piping. Emerging semantic segmentation methods demonstrate a level of versatility that could extend the capabilities of automated Scan-to-BIM well past the limited existing object categories. The accuracy of supervised deep learning methods in the context of 3D scene segmentation has experienced rapid improvement over the past year due to the recent availability of large, annotated datasets of indoor spaces. Unfortunately, the semantic object categories in the available datasets do not cover many essential BIM object categories, such as heating, ventilation and air-conditioning (HVAC), and plumbing systems. In an effort to leverage the success of deep learning for Scan-to-BIM, we present 3DFacilities, an annotated dataset of 3D reconstructions of building facilities. The dataset contains over 11,000 individual RGB-D frames comprising 50 scene reconstructions annotated with 3D camera poses and per-vertex and per-pixel annotations. Our dataset is available at https://thomasczerniawski.com/3dfacilities/.
12 citations
TL;DR: In this article, the authors investigate the potentials of RGB-D cameras in modeling building indoor environments and show that the camera can provide a stream of mid-accurate sensing data in real time.
Abstract: 3D as-built models of building indoor environments could be used to facilitate multiple building assessment and management tasks, such as post-disaster safety evaluation, renovation/retrofit planning, and maintenance scheduling. However, modeling building indoor environments is a challenging task. It is even more difficult than modeling building facades due to the issues, such as limited lighting conditions and prevalence of texture-poor walls, floors, and ceilings. This paper investigates the potentials of RGB-D cameras in modeling building indoor environments. Three pilot studies have been performed to evaluate 1) the accuracy of the sensing data provided by an RGB-D camera and 2) the automation that can be achieved for the registration of building indoor scenes and the recognition of building elements with the sensing data. The studies show that the camera can provide a stream of mid-accurate sensing data in real time. Also, a high degree of automation can be achieved through the fusion of spatial and visual data from the camera, when modeling the as-built conditions in building indoor environments.
12 citations
Cites background from "Automatic reconstruction of as-buil..."
...Meanwhile, the process of creating such models has been identified as labor-intensive and time-consuming (Tang et al. 2010)....
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TL;DR: The results indicated that the collaborations and cooperation among different institutions, countries, and authors are not close enough, and the most significant research and development in smart construction occurred primarily in the USA, China, and England.
Abstract: With the extensive development and application of information technologies in construction engineering and management (CEM), the construction site is experiencing a rapid digital revolution and transformation. Since smart construction site has become the current research trend and one of the most hot topics, thus this study adopted an integrated bibliometric approach and quantitative analysis to explore the global research on smart construction site. As it is indicated in the content, the bibliometric and scientometric method-based literature review was carried out in this study. To be specific, the co-citation analysis in terms of author, document, and journal; the collaboration analysis in terms of authorship, institutions, and country/region; and category analysis, as well as cluster analysis and burst analysis were conducted based on 2206 peer-reviewed academic papers, which were published from January 2000 to February 2021. It is found that there has been an explosion of relevant publications especially in the past 10 years along with the changing of keywords from flexibility approach to information technologies, 3D reconstruction, IoT technologies, virtual reality, and others. Moreover, the results indicated that the collaborations and cooperation among different institutions, countries, and authors are not close enough, and the most significant research and development in smart construction occurred primarily in the USA, China, and England. Additionally, the smart construction site’s relevant research in terms of publication of quantity was doubled every five years. In addition, the smart construction site relevant research has gradually changed from the traditional project performance associated indicators to smart simulation applications and scenes. Lastly, implementation and management-related concerns about smart construction sites are discussed with seven topics. This study provides researchers and practitioners not merely with an in-depth understanding of the characters and also the trend of smart construction site research in the construction engineering and management field.
12 citations
30 May 2018-ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
TL;DR: The automatic registration of terrestrial laser scans appears to be a solved problem in science as well as in practice but this assumption is questionable especially in the context of large projects where an object of interest is described by several thousand scans.
Abstract: . The automatic registration of terrestrial laser scans appears to be a solved problem in science as well as in practice. However, this assumption is questionable especially in the context of large projects where an object of interest is described by several thousand scans. A critical issue inherently linked to this task is memory management especially if cloud-based registration approaches such as the ICP are being deployed. In order to process even thousands of scans on standard hardware a plane-based registration approach is applied. As a first step planar features are detected within the unregistered scans. This step drastically reduces the amount of data that has to be handled by the hardware. After determination of corresponding planar features a pairwise registration procedure is initiated based on a graph that represents topological relations among all scans. For every feature individual stochastic characteristics are computed that are consequently carried through the algorithm. Finally, a block adjustment is carried out that minimises the residuals between redundantly captured areas. The algorithm is demonstrated on a practical survey campaign featuring a historic town hall. In total, 4853 scans were registered on a standard PC with four processors (3.07 GHz) and 12 GB of RAM.
12 citations
TL;DR: A new model for campus facility maintenance management is proposed that enables maintenance staff to maintain water dispensers at the optimal time and select the shortest maintenance path and an optimization algorithm developed by integrating Dijkstra’s algorithm, simulated annealing, and a genetic algorithm was used.
Abstract: Effective management for the maintenance of water dispensers dispersed throughout an academic campus is essential for ensuring the quality of drinking water. Conventionally, water dispenser maintenance is conducted approximately bimonthly or when a passive fault notice is obtained. This maintenance frequency usually results in ineffective allocation of maintenance staff and poor maintenance quality. This study proposes a new model for campus facility maintenance management that enables maintenance staff to maintain water dispensers at the optimal time and select the shortest maintenance path. The proposed model was developed using the maintenance information of the Construction Operations Building Information Exchange obtained from building information models of multiple buildings, water dispenser operation data from a water dispenser monitoring module, and an optimization algorithm developed by integrating Dijkstra’s algorithm, simulated annealing, and a genetic algorithm to identify the shortest maintenance path. The proposed model was tested on a campus in Northern Taiwan. The application results revealed that maintenance strategies could be systematically established to determine the optimal time to dispatch maintenance staff based on the lowest unit cost criterion; this approach was also used to identify the shortest maintenance path through multiple buildings.
12 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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