A SCAN-TO-BIM Workflow proposal for cultural heritage. Automatic point cloud segmentation and parametric-adaptive modelling of vaulted systems

Abstract. Cultural Heritage has been significantly impacted by advancements in the Information and Communications Technology domains, which have inspired a strong multidisciplinary interest and enabled the development of innovative strategies for the preservation, management, and enhancement of the heritage itself. Notably, the digitisation process, which entails the acquisition of 3D data obtained through cutting-edge LiDAR and photogrammetric scanning techniques, is set up as an advantageous tool for producing an accurate representation of the historical buildings. In addition, point clouds and reliable HBIM models have caught the minds of the architectural community, and are now receiving huge backing from Artificial Intelligence. Such support is provided by procedures that link semantic features to structural and decorative elements. In this scenario, the following research is presented: the aim is to test an automated iterative process within a scan-to-BIM methodology, starting from automatic point cloud segmentation operations with open-source, model-fitting algorithms. This method will prove to be a solid support for the final phase of the 3D parametric/adaptive reconstruction that’s also compatible with BIM Authoring. The study focuses on various masonry vaulted systems. These types of structures are first examined using ideal models, which were perfectly discretised and set up by the user, and then employed as a starting point for validating the parameters of the RANSAC algorithm on point clouds acquired by laser scanners. These latter ones nevertheless have irregular geometries, making comprehension, analysis, and management far more challenging

AUTOMATIC POINT CLOUD SEGMENTATION FOR THE DETECTION OF ALTERATIONS ON HISTORICAL BUILDINGS THROUGH AN UNSUPERVISED AND CLUSTERING-BASED MACHINE LEARNING APPROACH

Abstract. The article describes an innovative procedure for the three-dimensional analysis of decay morphologies of ancient buildings, through the application of machine learning methods for the automatic segmentation of point clouds. In the field of Cultural Heritage conservation, photogrammetric data can be exploited, for diagnostic and monitoring support, to recognize different typologies of alterations visible on the masonry surface, starting from colour information. Actually, certain stone and plaster surface pathologies (biological patina, biological colonization, chromatic alterations, spots,…) are typically characterized by chromatic variations. To this purpose, colour-based segmentation with hierarchical clustering has been implemented on colour data of point clouds, considered in the HSV colour-space. In addition, geometry-based segmentation of 3D reconstructions has been performed, in order to identify the main architectural elements (walls, vaults), and to associate them to the detected defects. The proposed workflow has been applied to some ancient buildings' environments, chosen because of their irregularity both in geometrical and colorimetric characteristics

ACCURACY EVALUATION OF SMARTPHONE-BASED VIDEOGRAMMETRY FOR CULTURAL HERITAGE DOCUMENTATION PROCESS

The last decade has seen the development of a growing tendency to use the most modern technologies, in the field of Cultural Heritage, with the aim of digitizing and facilitating protection and conservation activities. Much research has focused on the development of innovative methods such as photogrammetry or Terrestrial Laser Scanners, in terms of reliability, precision, time and costs. In this research, however, the use of the smartphone was investigated by comparing the point clouds obtained via videogrammetry from smartphones, with those generated by different digital survey techniques, such as Terrestrial Laser Scanners and photogrammetry via SLR camera. Specifically, a smartphone was used and the comparison between point clouds was conducted based on four criteria: point clouds fitting, density evaluation, profiling and texture quality with the aim, therefore, of verifying the geometric reliability of the data and the quality of polygonal lines and the mesh/texture derived. The case study selected was the sepulchral monument of the Pascopepe Lambertini family (14th century), located in the Crypt of Santa Maria della Scala, the Cathedral of Trani (South of Italy). Finally, the research demonstrates how this methodology, in the documentation of heritage, allows for even greater portability and accessibility compared to other methodologies, maintaining widely acceptable standards of accuracy and therefore going to constitute a valid alternative in the documentation of historical heritage