Roof Reconstruction from Point Clouds using Importance Sampling

Roof Reconstruction from Point Clouds using Importance Sampling

Blog Article

We propose a novel fully automatic technique for roof fitting in 3D point clouds based on sequential importance sampling (SIS).Our approach makes no assumption of the nature cards (sparse, dense) or origin (LIDAR, image matching) of the point clouds and further distinguishes, automatically, between different basic roof types based on model selection.The algorithm comprises an inherent data parallelism, the lack of which has been a major drawback of most outdoor dining table Monte Carlo schemes.

A further speedup is achieved by applying a coarse to fine search within all probable roof configurations in the sample space of roofs.The robustness and effectiveness of our roof reconstruction algorithm is illustrated for point clouds of varying nature.