Jul 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· 0 citations· 4 references
Abstract
Abstract. This paper presents a semi-automated pipeline for extracting architectural plans from terrestrial LiDAR point clouds of archaeological sites characterized by irregular geometries and significant surface degradation. The proposed workflow converts dense three-dimensional data into simplified two-dimensional representations by combining geometric alignment, expert-guided cross-section selection, feature detection using Intrinsic Shape Signatures (ISS), region-based segmentation, and polyline simplification. The method is specifically designed to handle rock-cut tomb environments, where erosion, noise, and non-planar surfaces complicate conventional Scan-to-Plan approaches. The pipeline is evaluated on six tombs from the Sheikh Said necropolis in Middle Egypt, covering a range of architectural configurations and preservation states. Results demonstrate that the method efficiently produces CAD-compatible outlines that capture the dominant structural geometry while significantly reducing manual drafting time. However, the accuracy of the generated plans depends on surface conditions, with degraded or ornamented areas introducing geometric artifacts that require expert refinement. The proposed approach provides a robust geometric baseline for archaeological documentation and highlights the potential of human-in-the-loop workflows for complex heritage environments.
Abstract. This paper presents a comprehensive methodology for the automated semantic segmentation and 3D reconstruction of industrial building elements, including roof panels, floor, rafters, purlins, and columns, from unstructured point clouds. The proposed approach integrates orientation-based filtering, projection onto characteristic planes, morphological analysis, and optimization-based I-profile fitting to generate accurate 3D models. The workflow begins with point cloud preprocessing, where the data are aligned with the building axes and cleaned of outliers, followed by subdivision into two subsets based on local surface orientation. Binary projections are then processed to extract element contours, while roof slopes and panel inclinations are automatically estimated to guide the reconstruction of rafters and purlins. The method was validated on a real-case study of 930 m² industrial warehouse scanned with a mobile laser scanner, resulting in a raw dataset of seven million points. The segmentation achieved F1-scores above 0.90 for floors, roof panels, rafters, and columns, and 0.75 for purlins. Profile fitting yielded an average width error of 3.8%, confirming the robustness and reliability of the reconstruction across diverse structural components.
P. González-Cabaleiro, M. Albadri, Antonio Fernández et al.· The International Archives o...· 0 citations
Abstract. The 3D documentation of complex scenes—characterized by restricted spaces, irregular geometries, and poor lighting—remains a significant challenge in cultural heritage. This study proposes a rapid data acquisition methodology based on the multi-sensor fusion of Terrestrial Laser Scanning (TLS) and Spherical Photogrammetry (SP). The approach was validated in two distinct complex environments: an ancient Egyptian rock-cut tomb (QH36, Aswan, Egypt) and a natural Iberian sanctuary cave (Cueva de la Lobera, Jaén, Spain). The methodology uses TLS to establish a high-precision geometric backbone, achieving registration errors below 0.5 cm. By extracting Ground Control Points (GCPs) directly from the TLS point cloud, the reliance on traditional total station surveying was significantly reduced, enhancing fieldwork efficiency. SP was implemented to obtain realistic textures and to support geometry by using a 360-degree multi-camera with integrated LED lighting, providing full spherical coverage and high-resolution textures. Results indicate that SP is at least six times faster than conventional photogrammetry. Furthermore, the use of TLS-derived meshes enabled advanced digital masking to remove non-interest objects (e.g., archaeological equipment) from the final models. While conventional photogrammetry remains the benchmark for fine architectural details, this research demonstrates that the TLS-SP fusion is the most viable solution for the rapid, high-accuracy documentation of constrained heritage sites. This hybrid workflow ensures geometric integrity while drastically reducing acquisition times, providing a robust framework for future archaeological and conservation projects.
A. Mozas-Calvache, José Luis Pérez-García, J. M. Gómez-López et al.· The International Archives o...· 0 citations
The results demonstrate the potential of hybrid AI and geometric approaches to improve the efficiency, repeatability, and reliability of Scan-to-BIM processes for historical masonry bridge heritage and show that the geometric quality of the HBIM model depends primarily on the density, spatial distribution and completeness of the structural points, rather than on their total number.
V. Alfio, Massimiliano Pepe, Donato Palumbo et al.· Applied Sciences· 0 citations
An adaptive neighborhood scale selection method for local PCA, designed for robust edge extraction from large-scale 3D scanned point clouds, and the use of octree-based spatial indexing ensures computational efficiency, making the method practical for field-based heritage conservation and structural analysis on consumer-grade hardware.
Tomoya Okajima, Satoshi Takatori, F. I. Thufail et al.· The International Archives o...· 0 citations
Archaeological feature detection at complex, mixed-environment sites requires accurate, efficient methods for identifying subtle morphological signatures. This study presents a semi-automated remote sensing pipeline for the detection and delineation of archaeological earthworks at Cahokia Mounds (Illinois, USA), a major Mississippian urban center and UNESCO World Heritage Site. Three LiDAR datasets, two collected via UAV-mounted sensors and one from a piloted aircraft survey, were processed into Digital Terrain Models and transformed into Local Relief Models (LRM). K-means clustering was applied to segment the LRMs into feature classes, followed by contour bounding using the OpenCV library to outline mounds and borrow pits. Additionally, SAR-derived Local Incidence Angle (LIA) rasters from PALSAR-3 and Sentinel-1 were processed through angular deviation mapping to identify slope anomalies associated with archaeological features. Results across all five datasets demonstrate the complementary strengths of LiDAR and SAR: LiDAR excels at resolving elevation-defined features such as mound footprints, while LIA captures directional slope behavior that highlights mound edges, borrow pit rims, and linear features such as causeways. Comparative analysis of LiDAR acquisition frequencies reveals minimal differences in archaeological feature recovery between pulse settings, suggesting that sensor platform choice matters more than power-density tradeoffs for this application. Despite the need for human review to filter modern disturbances and natural false positives, the integrated workflow meaningfully accelerates prospection and reduces interpretive subjectivity. The methods are scalable, site-invariant, and work with open-access data, making them applicable to archaeological landscapes worldwide.
J. Vilbig, V. Sagan, Joseph A. Jilek et al.· Remote Sensing· 0 citations
The first results of the AI-based processing pipeline developed within the HERITALISE project are presented, applied to three multiscale case studies at the Reggia di Venaria Reale, demonstrating strong photorealistic rendering capabilities, particularly for complex material properties and geometrically challenging interiors, whilst highlighting current limitations for metric surveying applications.
F. Chiabrando, A. Lingua, Alessio Martino et al.· The International Archives o...· 0 citations