Adaptive Partitioning of Urban Facades

Automatically discovering high-level facade structures in unorganized 3D point clouds of urban scenes is crucial for applications like digitalization of real cities.This work introduces the concept of adaptive partitioning to automatically derive a flexible and hierarchical representation of 3D urban facades.Our key observation is that urban facades are largely governed by concatenated and/or interlaced grids.Hence,unlike previous automatic facade analysis works which are typically restricted to globally rectilinear grids,we propose to automatically partition the facade in an adaptive manner.The concept of adaptive partitioning is also applicable to flexible and robust analysis of image facades.We evaluate our method on a dozen of LiDAR scans of various complexity and styles,and the image facades from the eTRIMS database and the Ecole Centrale Paris database.A series of applications that benefit from our approach are also demonstrated.