Deepwater Archaeological Survey: An Interdisciplinary and Complex Process

摘要: This chapter introduces several state of the art techniques that could help to make deep underwater archaeological photogrammetric surveys easier, faster, more accurate, and provide visually appealing representations in 2D 3D for both experts public. We detail how captured data is analysed then represented using ontologies, this facilitates interdisciplinary interpretation cooperation. Towards automation, we present a new method adopts learning approach detection recognition objects interest, amphorae example. In order readable, direct clearer illustrations, describe generate different styles sketches out orthophotos developed neural networks. same direction, Non-Photorealistic Rendering (NPR) technique, which converts model into readable representation useful communicate simplifies identification interest. Regarding public dissemination, demonstrate recent advances virtual reality an high resolution, amusing appropriate visualization tool offers possibility ‘visit’ unreachable site. Finally, conclude by introducing plenoptic approach, promising technology can change future photogrammetry making it easier less time consuming allows user create only one camera shot. Here, introduce concepts, developing process, some results, obtained with imaging.