MLS2LoD3: Refining low LoDs building models with MLS point clouds to
  reconstruct semantic LoD3 building models
Olaf Wysocki Ludwig Hoegner Uwe Stilla
Although highly-detailed LoD3 building models reveal great potential in
various applications, they have yet to be available. The primary challenges in
creating such models concern not only automatic detection and reconstruction
but also standard-consistent modeling. In this paper, we introduce a novel
refinement strategy enabling LoD3 reconstruction by leveraging the ubiquity of
lower LoD building models and the accuracy of MLS point clouds. Such a strategy
promises at-scale LoD3 reconstruction and unlocks LoD3 applications, which we
also describe and illustrate in this paper. Additionally, we present guidelines
for reconstructing LoD3 facade elements and their embedding into the CityGML
standard model, disseminating gained knowledge to academics and professionals.
We believe that our method can foster development of LoD3 reconstruction
algorithms and subsequently enable their wider adoption.