SimpliCity: Reconstructing Buildings with Simple Regularized 3D Models

Jean-Philippe Bauchet, Raphael Sulzer, Florent Lafarge, Yuliya Tarabalka; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, pp. 7616-7626

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. The two key ideas are first to regularize not the 3D planes as commonly done in the literature but a 2D polyhedral partition constructed from the planes and second to 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.