Steps in Improving 3D Reconstruction in Submerged Worlds by Dimitrios Skarlatos

Improving 3D reconstruction in the submerged world is a fascinating challenge that combines technological innovation and scientific understanding. In this brief presentation the motivation and need of underwater 3D reconstruction will be established under the scope of archaeological excavation in Mazotos shipwreck site. The challenges that underwater environment poses, the inherent restrictions due to water properties, illumination conditions, and depth will be briefly described. The advancements will focus on the development of a low cost ROV, able to perform data acquisition for 3D reconstruction. The main needs for such an ROV will be presented along with the design decisions taken to fulfill them. The second part of the presentation will be devoted in a novel machine learning approach to restore color formation without any external information, in depths where artificial lighting is necessary. Instead of using artificial data as training data for ML, a novel approach has been developed, which derives training data from the 3D reconstruction data set itself. This approach makes the proposed methodology self-adaptive to environmental conditions and camera-lights combination. It is also versatile enough to be applied on archive data, just like the data used so far for its development.