/A, 9-11 Nov. 1999
SEMI-AUTOMATIC
ONSTRUCTION
3D Primitive
description
Primitive surface
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tomatic and semi-automatic
the reconstruction algorithm.
n the right and the flash icon
tically derived data can be
' starts by decomposing the
nitives (rectangles). Each 2D
esponding 3D primitive. The
of the 2D primitive applies as
'emains to be determined are
y roof type (currently one of
> building and roof slope. A
the best fit of the models to
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International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 3W14, La Jolla, CA, 9-11 Nov. 1999
Figure 6: Reconstructed building and DSM
After this step, the individually reconstructed primitives are
overlapping 3D solids. They can be output in the form of either
a list of solid descriptors or a list of planar faces. Most often it is
desirable to find a building description without overlapping
parts. As this is a standard CSG problem, a CAD kernel is used
to perform the necessary merging (Boolean union) operations.
Finally, a non-overlapping building description is obtained,
which can be exported an converted into different CAD formats.
147
The different steps of the algorithm are exemplary depicted in
figures 3 to 6. Figure 3 shows the ground plan of the building
after decomposition in different rectangles. Each rectangle
triggers the reconstruction of a corresponding primitive (
Figure 4). For that purpose roof type, roof height and eaves
height are estimated by minimizing the differences between the
DSM surface and the 3D primitive. In order to generate a
boundary representation, a union of the reconstructed primitives
is performed in the final step (
Figure 5).
Figure 6 again shows the result of the reconstruction process
and the DSM surface used for reconstruction overlaid.
The result of the procedure for a larger area is depicted in
Figure 7. This test site is located in the city of Stuttgart. It
covers an area of 1.8 km x 2.3 km and contains 5208 buildings,
which were reconstructed automatically. For this area the
groundplans were provided from an digitization of a 1:500 map
or were derived from the original measurements. This digital
data set is already available for the complete city of Stuttgart.
Almost all buildings could be reconstructed by the automatic
procedure with sufficient accuracy. Gross errors in the
reconstructed roof shape are only visible for singular buildings.
These errors were mainly caused by court yards of buildings,
which were not represented properly in the available 2D GIS.
Incorrect results can also occur, if parts of the building, like a
bay or a dormer window are not represented by the ground plan
and therefore can not be reconstructed by the automatic
procedure. In this case a manual editing is required in order to
correct or refine the result of automatic reconstruction.
For that purpose an interactive tool for the modification of the
ground plans is available. The tool allows to define, delete and
modify 2D building primitives. Using the same algorithms as
those employed in the fully automatic process, three-
dimensional primitives are reconstructed instantly when the user
modifies the underlying 2D geometry. In order to support the
interpretation of the scene by the operator, the editing tool
enables the simultaneous display of 2D ground plans and
primitives in an arbitrary number of images, like a scanned map,
an ortho image or a greyvalue-coded DSM. Beside that, a 3D
rendered display shows part of the DSM in the vicinity of the
selected building and the current 3D building reconstruction. A
more detailed description of the complete algorithm can be
found in Haala and Brenner (1999).
4 VISUALIZATION
The generation of realistic visualizations as the final goal of our
approach presumes the application of image texture. This is also
advantageous since the use of natural texture can substitute the
geometric modeling of building parts at least to a certain extend.
A realistic impression can for example already be achieved if an
image of a facade is mapped to the corresponding planar surface
of the reconstructed building. In this case a geometric
reconstruction of the different windows is no longer required.
The mapping of image texture to the corresponding surfaces of
the reconstructed buildings can for example be realized if aerial
images are available in addition to the already used DSM and
groundplans. After reconstruction the wireframes of the
buildings can be projected into the aerial images and the
required texture can be extracted and mapped to the
corresponding surface patches. This procedure, which was also
applied for the generation of Figure 8 is usually sufficient, if
image texture is only required for the roofs of the buildings and
the terrain surface. In order to provide texture for the facades of
