城市建筑点云的自适应分割方法

自动地提取城市建筑点云数据中的高层次结构是城市数字化等应用的重要基础步骤.通过提出"自适应分割"的概念来自动地获取三维城市建筑点云的一种灵活、层次化的结构表示.由于城市建筑的单元分布大都呈一种级联或者交错的形式,与之前采用全局规则格点进行分析的方法不同,文中采用一种自适应的方法对建筑点云进行分析;也可将自适应分割的概念用于建筑图像的分析上.最后给出了在不同类型的建筑点云和图像进行分析的结果以及一些相关的应用.

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.