2019
DOI: 10.3390/rs11091102
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Automatic Recognition of Common Structural Elements from Point Clouds for Automated Progress Monitoring and Dimensional Quality Control in Reinforced Concrete Construction

Abstract: This manuscript provides a robust framework for the extraction of common structural components, such as columns, from terrestrial laser scanning point clouds acquired at regular rectangular concrete construction projects. The proposed framework utilizes geometric primitive as well as relationship-based reasoning between objects to semantically label point clouds. The framework then compares the extracted objects to the planned building information model (BIM) to automatically identify the as-built schedule and… Show more

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Cited by 97 publications
(98 citation statements)
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“…A very general division of point cloud segmentation and classification is given in [24], in which the existing algorithms are divided into either the use of geometric axioms and mathematical functions, or the use of machine learning techniques. This division is concurrent with ideas presented by [25], in which the former is mentioned as the use of geometrical, spatial, and contextual constraints. The authors in [26] mentioned a distinction between heuristic and machine learning techniques.…”
Section: Point Cloud Processingmentioning
confidence: 77%
See 3 more Smart Citations
“…A very general division of point cloud segmentation and classification is given in [24], in which the existing algorithms are divided into either the use of geometric axioms and mathematical functions, or the use of machine learning techniques. This division is concurrent with ideas presented by [25], in which the former is mentioned as the use of geometrical, spatial, and contextual constraints. The authors in [26] mentioned a distinction between heuristic and machine learning techniques.…”
Section: Point Cloud Processingmentioning
confidence: 77%
“…While the appeal of machine learning is strong for performing point cloud processing in the case of complex geometries as encountered in heritage objects, the main bottleneck remains the generation of the training dataset [25]. In this paper, an algorithmic approach is considered in order to provide a fast result which may eventually be used to help generate training data for future machine learning techniques.…”
Section: Machine Learning and Deep Learning Approachesmentioning
confidence: 99%
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“…The reason for this is that certain BIM platforms, e.g., ArchiCAD®or Autodesk Revit® [34], enable the insertion of 2D drawings in PDF format. There are other works that addressed mesh or point cloud conversion algorithms to improve 3D elements in newly constructed buildings [35][36][37][38] and heritage buildings [8,9,27,39]. produced parametric objects with geometrical alterations and further information under the HBIM approach.…”
mentioning
confidence: 99%