` Initial Interaction

Initial Interaction

First the user classifies the detection problem: dark areas, poor contrast, occluded buildings, occluded shadows, partly detected L or T-buildings (this list can be extended). The classification scheme depends on the performance of the automated system. This qualitative information is very useful to constraint the search for new hypotheses. Although the classification is in general not unique (usually several problems occur at the same time), it is unlikely that a correct hypotheses will be rejected as long as the classification is correct.

The second qualitative step is a very rough localization of the missing building. This can be, for example, any point on the roof (it is possible to automate this step by clustering rejected hypotheses, see below). After the initial interaction the most likely hypothesis can be established by the additional information provided by the user.

Click on the boxes below to get example images or MPEG-movies

(Note that for the box Initial Interaction there is only an MPEG-movie describing the localization of a building. As mentioned above, also the classification of a detection problem is part of the Initial Interaction. But there is also a movie showing this.)