<p>Planning on adaptive reuse, maintenance and restoration of historic timber structuresrequiresextensive architectural and structural analysis of the actual condition. Current methods for a modellingof roof constructions consist of several manual steps  including  the  time-consuming  dimensional modelling. The  continuous  development  of terrestrial laser  scanners increases  the  accuracy,  comfort  and  speed  of  the  surveying  work inroof constructions. Resultingpoint  clouds enabledetailed visualisation of theconstructionsrepresented by single points or polygonal meshes, but in fact donot containinformation  about  the  structural  system  and  the  beam  elements.  The  developed  workflow  containsseveral  processing steps on the point cloud dataset. The most important among them arethenormal vector computation, the segmentation of points to extract planarfaces, a classification of planarsegmentsto detect the beam side facesand finally theparametric modelling of the beams on the basis of classified segments. Thisenablesa highly automated transitionfrom raw point cloud data to a geometric model containing beams of the structural system. The geometric model,as well as additional information  about  the  structural  properties  of involved wooden  beams  and  their  joints,is necessaryinput  for  a  furtherstructural modellingof timber constructions. The results of the workflow confirm that the proposed methods work well for beams  with a rectangularcross-section  and  minor  deformations. Scan  shadows  and occlusionof  beamsby additional installationsor interlockingbeamsdecreases  the  modelling  performance,  but  in generala high  level  ofaccuracy  and completeness isachieved ata high degree of automation</p><div data-canvas-width="62.83200000000001"><strong>Highlights:</strong></div><div data-canvas-width="62.83200000000001"> </div><div><ul><li><p>This article presents a novel approach to automated reconstruction of beam structures by modelling geometry from segmented point clouds.</p></li><li><p>Wooden beams are modelled as cuboids, thus a rectangular cross-section with minor deformation is required.</p></li><li><p>An accuracy of less than 1 cm can be reached for modelled beams, compared to the reference LiDAR point cloud.</p></li></ul></div>

ABSTRACT:The analysis of historic roof constructions is an important task for planning the adaptive reuse of buildings or for maintenance and restoration issues. Current approaches to modeling roof constructions consist of several consecutive operations that need to be done manually or using semi-automatic routines. To increase efficiency and allow the focus to be on analysis rather than on data processing, a set of methods was developed for the fully automated analysis of the roof constructions, including integration of architectural and structural modeling. Terrestrial laser scanning permits high-detail surveying of large-scale structures within a short time. Whereas 3-D laser scan data consist of millions of single points on the object surface, we need a geometric description of structural elements in order to obtain a structural model consisting of beam axis and connections. Preliminary results showed that the developed methods work well for beams in flawless condition with a quadratic cross section and no bending. Deformations or damages such as cracks and cuts on the wooden beams can lead to incomplete representations in the model. Overall, a high degree of automation was achieved.

We present a set of methods to improve the automation of the parametric 3D modeling of historic roof structures using terrestrial laser scanning (TLS) point clouds. The final product of the TLS point clouds consist of 3D representation of all objects, which were visible during the scanning, including structural elements, wooden walking ways and rails, roof cover and the ground; thus, a new method was applied to detect and exclude the roof cover points. On the interior roof points, a region-growing segmentation-based beam side face searching approach was extended with an additional method that splits complex segments into linear sub-segments. The presented workflow was conducted on an entire historic roof structure. The main target is to increase the automation of the modeling in the context of completeness. The number of manually counted beams served as reference to define a completeness ratio for results of automatically modeling beams. The analysis shows that this approach could increase the quantitative completeness of the full automatically generated 3D model of the roof structure from 29% to 63%.

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