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Our aim is to extract buildings from Digital Elevation Models.
To achieve this goal, we define a point process whose points
represent buildings. We then define a density for this point process
which is split into two parts. When written as an energy this density
consists of two fields :
- the first one is an "internal field" that allows us to model the prior
knowledge we have on patterns of buildings in urban areas. For
instance, we avoid overlapping buildings.
- the second one is an "external field" that makes the point process
fit the data, ie. the Digital Elevation Model.
Once we have defined this artificial likehood, we use a
Metropolis Hastings Green sampler, which is an extension of Geyer and
algorithm to sample point processes. This gives an estimate of the
observed urban area.
We present results on real data provided by the
French Mapping Institute (IGN).
Key words : Point process, RJMCMC, building extraction, Digital