基于线框分析方法的建筑物主体模型智能构建

Intelligent construction of main building structure model based on wireframe analysis

空间信息获取技术的发展推动了三维点云数据的建筑模型构建研究.然而,现有的模型构建方法大多依赖人工交互的方式,极高的人工和时间成本消耗不利于大范围城市模型的构建及应用.针对上述问题,本文提出一种基于线框分析的建筑物主体模型构建方法.首先对原始建筑物点云进行滤波与归一化处理,并提取建筑物的多层次边界多边形综合描述建筑边界结构;然后将各层次边界多边形分割出简单、易控的多个矩形基元,采用稳健的层次化矩形连接、分析算法生成完整的建筑物主体结构模型;最后通过对三组结构复杂、遮挡严重的建筑物点云数据的实验表明该方法具有良好的性能,可以稳健地处理存在数据缺失、点密度差异的建筑物点云数据,并且兼顾了建筑物不同高度上的结构差异性,实现了建筑物线框模型的高精度构建.

Architectural models can be constructed from 3D point cloud data due to the advances in spatial information acquisition technology.However,most of the existing model construction methods rely on manual interaction,which is extremely laborious and time consuming,thus are not applicable to the construction of large-scale urban models and related applications.This paper proposes an approach to build the main structure model based on wireframe analysis.First,filter and normalize the original building point cloud,and extract the multi-level boundary polygons of the building to comprehensively describe the building boundary structure;then divide the boundary polygons at each level into multiple rectangular primitives that are simple and easy to control.A robust hierarchical rectangular connection and analysis algorithm is used to generate a complete main structure model of the building.Finally,experiments on three sets of complex structure and severely occluded building point cloud data show that the approach has good performance and can robustly handle the point cloud data of buildings with missing data and different point density.The proposed approach takes into account the structural differences at different heights of the building,and realizes the high-precision construction of the wireframe model for the main building structure.