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: In this article , the authors investigate the research frontiers and knowledge structure in BIM-IoT integration and the relationship between BIM and sustainable building and explore the research hotspots, trends, and future research directions.
Abstract: Sustainable development, which has become the priority study of architectural design, is receiving increasing attention with global climate change. At the same time, the building industry is urgently changing towards intelligent and digitalized tendencies. As a result, Building Information Modeling (BIM) and the Internet of Things (IoT) make crucial contributions to the transforming process. However, there is little knowledge of the integration of BIM–IoT in sustainable building from a macro perspective. Moreover, most existing research adopts a literature review method and lacks objective quantitative analysis. Few papers use bibliometric analysis to study the respective BIM and IoT research fields. Furthermore, few studies use Citespace software tools to analyze the integrated application of BIM–IoT. Therefore, this paper aims to investigate the research frontiers and knowledge structure in BIM–IoT integration and the relationship between BIM-IoT and sustainable building and explore the research hotspots, trends, and future research directions. A quick and objective method was proposed to understand the research status of these new and rapidly developing fields. This paper uses topic search in the web of science core collection to obtain relevant literature and then uses Citespace for bibliometric analysis based on the literature review. Controlled terms and subject terms statistics from the Engineering Index core database search results are also used to briefly examine the fields’ research frontiers and hotspots as obtained from Citespace. The results show that: (1) The research on BIM–IoT integration focuses on building intelligence with BIM as the basis of application, and research on BIM–IoT integration within the field of sustainable building is currently focused on the first three phases of the life cycle. (2) The development of sustainable buildings needs to be considered on its human and social dimensions. BIM provides a platform for sharing information and communication among stakeholders involved in the building’s entire life cycle. At the same time, IoT allows occupants to better participate in buildings’ sustainable design and decision making. (3) In the future, more emerging technologies such as cloud computing and big data are required to better promote sustainable buildings and thus realize the construction of sustainable smart cities. At the same time, researchers should also pay attention to the sustainable transformation of existing buildings.
3 citations
TL;DR: In this paper , a new wall detection method in the indoor point clouds of buildings is presented, where the point clouds are segmented into horizontal layers, and a concept of continuous segments in a 2D grid representation is used to extract the footprints of the wall structures, and 2D blocks are projected into 3D space to obtain the wall segments in the initial 3D point cloud.
3 citations
TL;DR: In this paper , a model-based 3D scan planning method for modular components that ensures user-specified scan quality is proposed, which automatically computes the input parameters for the laser scanner (i.e., angular step and field of view) and optimal scan positions.
Abstract: Modular construction can improve construction performance (i.e., cost, schedule, and safety) by prefabricating modules at an off-site facility and installing them at a construction site. However, when defects of modules are not easily repairable on the construction site, they cause additional cost overruns and delays due to long lead times of refabrication and reshipment. Thus, quality assessment of modular components at the fabrication facility before shipment is very important. The current inspection practices rely on manual measurement, which can be imprecise, labor-intensive, and time-consuming. To address this issue, some research efforts are made on the module inspection techniques (e.g., estimates of geometric properties and surface quality) using laser-scanned data. The accuracy of these techniques relies on the quality (i.e., coverage and resolution) of the scan data. However, ensuring the consistent quality of data is a major challenge as there is little to no research on optimal scan planning for modular components. Therefore, this paper proposes a model-based 3D scan planning method for modular components that ensures user-specified scan quality. Given a 3D computer-aided design (CAD) or building information modeling (BIM) model, scanner property, and user’s quality requirement, this method automatically computes the input parameters for the laser scanner (i.e., angular step and field of view) and optimal scan positions. It also predicts the scan quality and shows the areas that will not meet the user requirement due to geometric constraints (i.e., self-occluded surfaces). This study was validated through two case studies using two modular-sized structures in a fabrication facility. The results showed that the scan planner is able to accurately predict the scanning quality and ensure that the output scan will meet the user quality requirement.
3 citations
01 Jan 2012
TL;DR: In this article, a model-based automatic object recognition and registration framework, Projection-Recognition-Projection (PRP), was introduced to assist heavy equipment operators in rapidly perceiving 3D working environment at dynamic construction sites.
Abstract: It has been a challenging subject to recognize dynamic objects from a scattered work environment because large and complex 3D site data obtained by a laser scanner makes it difficult to process itself in real or near real time. This thesis introduces a model-based automatic object recognition and registration framework, Projection-Recognition-Projection (PRP), to assist heavy equipment operators in rapidly perceiving 3D working environment at dynamic construction sites. In this study, a digital camera and a hybrid laser scanner were used to rapidly recognize and register dynamic target objects in a 3D space by separating target object's point cloud data from a background scene for a quick computing process. A smart scan data updating algorithm has been developed which only updates the dynamic target object's point cloud data while keeping the previously scanned static work environments. Extracted target areas containing 3D point clouds were orthographically projected into a series of 2D planes with a rotation center located in the target's vertical-middle line. Prepared 2D templates were compared to these 2D planes by extracting SURF (Speeded Up Robust Feature) features. Then, point cloud bundles of the target were recognized, and followed by the prepared CAD model's registration to the templates. The field experimental results show that the proposed PRP framework is promising and can significantly improve heavy construction equipment operations and automated equipment control by rapid modeling dynamic target objects in a 3D view. ii ACKNOWLEDGEMENTS Foremost, I would like to thank my advisor Dr. Yong Cho for his help and support of my study and research. His guidance helped me in all the time of research. I could not have imagined having a better advisor. for supporting me all the time. Special thank goes to Chao Wang who has helped me gather and analyze data with his best knowledge and experience in statistics. Last, but not the least, I am very grateful to my family, for supporting me throughout my life.
3 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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