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Behind the proposed method for planar face matching is
the idea that it is sufficient to find the minimum number of
good matches to reconstruct the target. This does not
mean that only one sufficient set of matches is
necessarily favoured. With the help of simple heuristics
we can choose several sets to define the plane equation.
Ultimately the algorithm might propose just one solution to
the user, or it might suggest a set of solutions from which
the user accepts the most correct one.
5. CONCLUSIONS
This paper studies the integration of solid modelling
techniques into photogrammetric mapping. The focus was
on the geometric modelling of buildings by boundary
models. The principles of boundary models have been
presented and the interactive creation of the model has
been discussed. The functionality of primitive modelling
tools has been illustrated. In the case of man-made
objects, close integration of modelling and mapping is
seen as a necessity in detailed mapping. The integration
eliminates the need for a separate step in which the solid
model of an object is parsed from a set of independent
geometric primitives. Solid modelling methods offer a
general data structure into which the data can be
collected. They form a good basis for mapping tools that
utilize geometric constraints and geometric reasoning.
A geometrically constrained image matching procedure
for matching lines in object space was described. The
method fulfils the common least squares matching
criterion, but was here formulated as a search task. The
proposed line matching procedure by search is capable of
making direct use of information from all images
containing the line. It was also shown how line matching
can be used in the geometrically constrained matching of
planar faces. Later the matching of planar faces will also
be implemented using least squares matching by search.
ACKNOWLEDGEMENTS
The author thanks Professor Tapani Sarjakoski for his
encouragement and advice.
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