3D Building Model Fitting Using A New Kinetic Framework

TL;DR

This paper introduces a novel kinetic framework for fitting 3D building models to point cloud data, simplifying topology management during optimization.

Contribution

The paper presents a new kinetic framework that automates topology adjustments, enabling efficient variational optimization of polyhedral building models from DEM point clouds.

Findings

Framework effectively manages topological changes during fitting

Enables continuous evolution of polyhedral models with simple faces

Improves accuracy and robustness of 3D building model fitting

Abstract

We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variational optimization. This new kinetic framework allows the manipulation of a bounded polyhedron with simple faces by specifying the target plane equations of each of its faces. It proceeds by evolving continuously from the polyhedron defined by its initial topology and its initial plane equations to a polyhedron that is as topologically close as possible to the initial polyhedron but with the new plane equations. This kinetic framework handles internally the necessary topological changes that may be required to keep the faces simple and the polyhedron bounded. For each intermediate configurations where the polyhedron looses the simplicity of its faces or its boundedness, the simplest topological modification that is able to reestablish the simplicity and the boundedness is performed.