  Automatic methods for reconstructing buildings from airborne LiDAR point
clouds focus on producing accurate 3D models in a fast and scalable manner, but
they overlook the problem of delivering simple and regularized models to
practitioners. As a result, output meshes often suffer from connectivity
approximations around corners with either the presence of multiple vertices and
tiny facets, or the necessity to break the planarity constraint on roof
sections and facade components. We propose a 2D planimetric arrangement-based
framework to address this problem. We first regularize, not the 3D planes as
commonly done in the literature, but a 2D polyhedral partition constructed from
the planes. Second, we extrude this partition to 3D by an optimization process
that guarantees the planarity of the roof sections as well as the preservation
of the vertical discontinuities and horizontal rooftop edges. We show the
benefits of our approach against existing methods by producing simpler 3D
models while offering a similar fidelity and efficiency.
