  Creating geometric abstracted models from image-based scene reconstructions
is difficult due to noise and irregularities in the reconstructed model. In
this paper, we present a geometric modeling method for noisy reconstructions
dominated by planar horizontal and orthogonal vertical structures. We partition
the scene into horizontal slices and create an inside/outside labeling
represented by a floor plan for each slice by solving an energy minimization
problem. Consecutively, we create an irregular discretization of the volume
according to the individual floor plans and again label each cell as
inside/outside by minimizing an energy function. By adjusting the smoothness
parameter, we introduce different levels of detail. In our experiments, we show
results with varying regularization levels using synthetically generated and
real-world data.
