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 new mesh-to-HBIM modeling workflow and an integrated BIM management system to connect HBIM elements and historical knowledge and a semantic model with object-oriented knowledge is developed by extending the capability of the BIM platform.
Abstract: Built heritage has been documented by reality-based modeling for geometric description and by ontology for knowledge management. The current challenge still involves the extraction of geometric primitives and the establishment of their connection to heterogeneous knowledge. As a recently developed 3D information modeling environment, building information modeling (BIM) entails both graphical and non-graphical aspects of the entire building, which has been increasingly applied to heritage documentation and generates a new issue of heritage/historic BIM (HBIM). However, HBIM needs to additionally deal with the heterogeneity of geometric shape and semantic knowledge of the heritage object. This paper developed a new mesh-to-HBIM modeling workflow and an integrated BIM management system to connect HBIM elements and historical knowledge. Using the St-Pierre-le-Jeune Church, Strasbourg, France as a case study, this project employs Autodesk Revit as a BIM environment and Dynamo, a built-in visual programming tool of Revit, to extend the new HBIM functions. The mesh-to-HBIM process segments the surface mesh, thickens the triangle mesh to 3D volume, and transfers the primitives to BIM elements. The obtained HBIM is then converted to the ontology model to enrich the heterogeneous knowledge. Finally, HBIM geometric elements and ontology semantic knowledge is joined in a unified BIM environment. By extending the capability of the BIM platform, the HBIM modeling process can be conducted in a time-saving way, and the obtained HBIM is a semantic model with object-oriented knowledge.
51 citations
TL;DR: It is confirmed that the Germanwings will not be able to field a team in the Eurovision Song Contest this year because of a lack of funds.
51 citations
TL;DR: In this paper, a pre-retrofit model that efficiently obtains and integrates multiple forms of building data as a critical step to develop a comprehensive understanding of a building to be renovated is presented.
Abstract: In response to rising energy costs and the impetus to reduce environmental impacts, upgrading the large building stock that is responsible for 40% of the total energy consumption to maximum energy efficiency is becoming an important task. Despite the many benefits associated with retrofit projects, they are still only slowly being implemented because of the many challenges that exist. One of these challenges is optimizing the decision between renovation scenarios based on economic and environmental goals, which can be made possible with an accurate pre-retrofit model. The intention of this paper is to introduce a pre-retrofit model that efficiently obtains and integrates multiple forms of building data as a critical step to develop a comprehensive understanding of a building to be renovated. Opportunities for utilizing building information modeling (BIM) and geographical information systems (GIS) for retrofitting projects were explored through the study of a historical campus building. With the use of as-is geometric data and as-is data, building data maps were obtained. The next step of this study is to use the model to conduct scenarios comparison and optimize renovation decision based on economic and environmental goals.
51 citations
TL;DR: The aim of this paper is to explore and retrace the milestone works on this crucial topic in order to identify the unsolved issues and to propose and test a unique and simple workflow practitioner centered and based on the use of the latest available solutions for point cloud managing into commercial BIM platforms.
Abstract: In recent years, we have witnessed a huge diffusion of building information modeling (BIM) approaches in the field of architectural design, although very little research has been undertaken to explore the value, criticalities, and advantages attributable to the application of these methodologies in the cultural heritage domain. Furthermore, the last developments in digital photogrammetry lead to the easy generation of reliable low-cost three-dimensional textured models that could be used in BIM platforms to create semanticaware objects that could compose a specific library of historical architectural elements. In this case, the transfer between the point cloud and its corresponding parametric model is not so trivial and the level of geometrical abstraction could not be suitable with the scope of the BIM. The aim of this paper is to explore and retrace the milestone works on this crucial topic in order to identify the unsolved issues and to propose and test a unique and simple workflow practitioner centered and based on the use of the latest available solutions for point cloud managing into commercial BIM platforms. © 2016 SPIE and IS&T
50 citations
TL;DR: A full-fledged laser scanning framework for geometric data acquisition, comprising the entire spectrum from planning, surveying and data analysis is introduced, that details the necessary steps to acquire a point cloud that is applicable to BIM modelling.
Abstract: Laser scanning, as a rising topic within the Architecture, Engineering and Construction (AEC) industry, has been increasing both in importance and practice as a means of gathering in-situ geometric data. Several studies have covered possible applications of this technology, from construction monitoring to damage assessment, with Building Information Modelling (BIM) being one of its focus. Despite this, to present, no research was found to fully explore the laser scanning survey process, with most studies either focusing the process after the point cloud acquisition or after its conversion to BIM. To help fill this knowledge gap, the present article introduces a full-fledged laser scanning framework for geometric data acquisition, comprising the entire spectrum from planning, surveying and data analysis. The result is a framework that details the necessary steps to acquire a point cloud that is applicable to BIM modelling. The framework is validated through its application to a recently renewed bus station in Porto, Portugal. Relevant conclusions regarding setting selection, station positioning, optimization, point cloud decimation and treatment, required resolution, along other topics, are drawn through laboratory tests and the previously mentioned case study.
50 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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