Underwater Photogrammetry and Object Modeling: A Case Study of Xlendi Wreck in Malta

Abstract

In this paper we present a photogrammetry-based approach for deep-sea underwater surveys conducted from a submarine and guided by knowledge-representation combined with a logical approach (ontology). Two major issues are discussed in this paper. The first concerns deep-sea surveys using photogrammetry from a submarine. Here the goal was to obtain a set of images that completely covered the selected site. Subsequently and based on these images, a low-resolution 3D model is obtained in real-time, followed by a very high-resolution model produced back in the laboratory. The second issue involves the extraction of known artefacts present on the site. This aspect of the research is based on an a priori representation of the knowledge involved using systematic reasoning. Two parallel processes were developed to represent the photogrammetric process used for surveying as well as for identifying archaeological artefacts visible on the sea floor. Mapping involved the use of the CIDOC-CRM system (International Committee for Documentation (CIDOC)—Conceptual Reference Model)—This is a system that has been previously utilised to in the heritage sector and is largely available to the established scientific community. The proposed theoretical representation is based on procedural attachment; moreover, a strong link is maintained between the ontological description of the modelled concepts and the Java programming language which permitted 3D structure estimation and modelling based on a set of oriented images. A very recently discovered shipwreck acted as a testing ground for this project; the Xelendi Phoenician shipwreck, found off the Maltese coast, is probably the oldest known shipwreck in the western Mediterranean. The approach presented in this paper was developed in the scope of the GROPLAN project (Généralisation du Relevé, avec Ontologies et Photogrammétrie, pour l'Archéologie Navale et Sous-marine). Financed by the French National Research Agency (ANR) for four years, this project associates two French research laboratories, an industrial partner, the University of Malta, and Texas A & M University.

Validation of Geodetic Seafloor Benchmark Stability Using Structure‐From‐Motion and Seafloor Pressure Data

“…Surveys with similar levels of precision and durations would provide a great utility to and reduce the costs of marine geodetic surveys. However, their use in the marine environment is still relatively nascent and so far, has been limited to archaeological, biological, and relatively coarse mapping (Bennecke et al, 2016;Burns et al, 2015;Drap et al, 2015;Kwasnitschka et al, 2012;Westoby et al, 2012). In conjunction with other geodetic methods in the marine environment, SfM photogrammetry also has the potential to improve large-scale mapping, imaging, and navigation (Escartín et al, 2008;Kwasnitschka et al, 2016).…”

Georeferenced underwater photogrammetry to map marine habitats and submerged artificial structures

“…Aerial photogrammetry has been commonly used over the last two decades to map landscapes with airborne platforms such as unmanned aerial vehicles (UAVs or drones) (Honkavaara et al., ). Derived from the techniques developed through terrestrial and aerial methodology, close range underwater photogrammetry by scuba diving has, over the past few years, become a common tool for mapping marine archaeological sites and creating 3D models of underwater artefacts (Balletti et al., ; Drap et al., ). Indeed, its early usages date back several decades, as exemplified by Pollio (), Höhle () and Leatherdale and Turner ().…”

Virtual simulation of a late antique shipwreck at Marzamemi, Sicily: Integrated processes for 3D documentation, analysis and representation of underwater archaeological data

“…Such systems are still not without ongoing complications, but digital recording has rapidly become a mainstay for precise documentation of individual objects as well as broad threedimensional (3D) survey across entire submerged sites and surrounding topography (e.g. Balletti, Beltrame, Costa, Guerra, & Vernier, 2015;Demesticha, Skarlatos, & Neophytou, 2014;Drap et al, 2015;Fulton et al, 2016;Henderson, Pizarro, Johnson-Roberson, & Mahon, 2013;Martorelli, Pensa, & Speranza, 2014;McCarthy & Benjamin, 2014).…”