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: This work describes a method for converting unorganized point cloud data from 3D sketching into an explicit 3D model, contributing to closing the knowledge gap in transferring 3D sketches from a co-creator to an explicit model.
Abstract: This work describes a method for converting unorganized point cloud data from 3D sketching into an explicit 3D model, contributing to closing the knowledge gap in transferring 3D sketches from a co...
3 citations
Abstract: Intercomparison among six terrestrial laser scanner systems focused on the measurement of small elements ( < 0.5 m) is performed. Phase shift (PS) and time of flight (ToF) scanners are considered. Two standard artefacts containing three-dimensional printing spheres and steps of variable height are used for the experiment. Results show errors between −4.5 and 3.5 mm in the measurement of distances between step planes. The most stable systems for measuring small elements seem the Leica C10, Faro Photon and Riegl LMS Z390i. The quality of the results is linked to the overall quality of the system rather than the specific technology used for range measurement (PS or ToF) which does not appear to be a determining factor.
3 citations
TL;DR: This paper presents the method and findings of a visual knowledge domain map used to explore the development and evolution of Building information modeling technology.
Abstract: This paper presents the method and findings of a visual knowledge domain map used to explore the development and evolution of Building information modeling (BIM) technology. Metadata taken from 806...
3 citations
TL;DR: It can be concluded that computer vision is a key axis of improvement in construction management processes and other problems in the construction area and newcomers to this research field understand knowledge structure and formulate research directions, thereby enhancing knowledge development.
Abstract: In the construction area, visuals such as drawings, photos, videos, and 3D models, play a significant role in the design, build and maintenance of a facility, bringing efficiency to generate, transfer, and store information. Advanced visual computing techniques facilitate the understanding of design contents, work plans, and other types of information shared in the construction industry. Automatic visual data collection and analysis provide many possibilities to the construction industry and a large number of works have investigated how visual computing can improve construction management processes and other problems in the construction area. However, a comprehensive literature review is needed. This study uses bibliometric approaches to review the works published to date, and analyses the development of knowledge, significant research results, and trends. The purpose of this study is to help newcomers to this research field understand knowledge structure and formulate research directions, thereby enhancing knowledge development. From this study, it can be concluded that computer vision is a key axis of improvement. Moreover, building information modeling, laser scanning, and other visualization-related techniques are also important in advancing the construction area.
3 citations
01 Jan 2014
TL;DR: Adaptive Part Variation (APV) as discussed by the authors is a method where robotically automated fabrication and construction processes employ sensors and feedback to make real-time corrections to material and assembly processes by varying the geometry and location of future parts.
Abstract: This chapter introduces the concept of Adaptive Part Variation (APV) as a method where robotically automated fabrication and construction processes employ sensors and feedback to make real-time corrections to material and assembly processes by varying the geometry and location of future parts to respond to deviations between digitally defined and physically accumulating form. The potential disciplinary implications of the method are described followed by a comparison to existing approaches to providing tolerance for dimension error in architecture. As a case study, the material system of cold bending steel rod is utilized to investigate strategies for implementing Adaptive Part Variation within a fabrication workflow that includes the production, handling, and assembly of uniquely bent parts through synchronized robotic tasks and iterative sensor feed- back. Two computer vision systems are compared to assess their value for APV processes. Finally, potential shifts in the deployment of procedural design meth- odologies are discussed in relation to adaptive automated construction processes.
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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