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2022
Conference Paper
Title
Geospecific terrain databases for military simulation environments
Abstract
This paper discusses a rapid workflow for the automated generation of geospecific terrain databases for military simulation environments. Starting from photogrammetric data products of an oblique aerial camera, the process comprises deterministic terrain extraction from digital surface models and semantic building reconstruction from 3D point clouds. Further, an efficient supervised technique using little training data is applied to recover land classes from the true-orthophoto of the scene, and visual artifacts from parked vehicles to be separately modeled are suppressed through inpainting based on generative adversarial networks. As a proof-of-concept for the proposed pipeline, a dataset of the Altmark/Schnoeggersburg training area in Germany was prepared and transformed into a ready-to-use environment for the commercial Virtual Battlespace Simulator (VBS). The obtained result got compared to another automatedly derived database and a semi-manually crafted scene regarding visual accuracy, functionality and necessary time effort.
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