In this thesis, we present a fast approach to automated
generation of textured 3D city models with both high details at
ground level and complete coverage for birds-eye view.
A ground-based facade model is acquired by driving a vehicle
equipped with two 2D laser scanners and a digital camera under
normal traffic conditions on public roads. One scanner is
mounted horizontally and is used to determine the approximate
component of relative motion along the movement of the
acquisition vehicle via scan matching; the obtained relative
motion estimates are concatenated to form an initial path.
Assuming that features such as buildings are visible from both
ground-based and airborne view, this initial path is globally
corrected by Monte-Carlo Localization techniques using an aerial
photograph or a Digital Surface Model as a global map. The
second scanner is mounted vertically and is used to capture the
3D shape of the building facades. Applying a series of automated
processing steps, a texture-mapped 3D facade model is
reconstructed from the vertical laser scans and the camera
images. In order to obtain an airborne model containi ... mehrng the roof
and terrain shape complementary to the facade model, a Digital
Surface Model is created from airborne laser scans, then
triangulated, and finally texturemapped with aerial imagery.
Finally, the facade model and the airborne model are fused
to one single model usable for both walk- and fly-thrus. The
developed algorithms are evaluated on a large data set acquired
in downtown Berkeley, and the results are shown and discussed.