基于点云分割的建筑物立面结构提取方法
Building Facade Structure Extraction Method Based on Point Cloud Segmentation
江旭 1敖建锋 1邹永康1
作者信息
- 1. 江西理工大学土木与测绘工程学院,江西赣州 341000
- 折叠
摘要
建筑物立面结构是描述建筑模型的重要特征之一.为解决现有算法对建筑物立面结构提取时间长、空间投影错误和转换后点云缺失等问题,提出一种基于点云分割的建筑物立面结构提取方法.该方法采用单体化聚类分割提取窗户,通过点云降采样算法稀释主体结构以减少点云密度和复杂度;引入法向量算法实现高密度主体点云到边缘点云的提取;通过改进后的三维线段检测算法遍历边缘点云,实现建筑立面结构特征提取.通过自测点云和Semantic3D公开数据的对比试验,结果表明,所提方法能有效提取建筑立面结构,提高效率并更好地滤除无序线段,为点云立面处理和模型构建提供了一种新的结构处理方法.
Abstract
The building facade structure is one of the essential features to describe the architectural model.To solve the prob-lems of the existing algorithms such as the long time to extract the building facade structure,the spatial projection error,and the missing point cloud after conversion,this paper proposes a building facade structure extraction method based on point cloud segmentation.This method uses single clustering segmentation to extract windows,and dilutes the main structure through a point cloud Downsampling algorithm to reduce the density and complexity of point clouds.Introduce standard vector algorithm to remove high-density main point cloud to edge point cloud.Finally,the improved 3D line segment detection algorithm traver-ses the edge point cloud to achieve feature extraction of building facade structures.Comparative experiments using self-testing point clouds and Semantic 3D publicly available data demonstrate that the proposed method effectively extracts building facade structures,enhances efficiency,and improves the filtering of disordered line segments.This method offers a new approach for structural processing in point cloud facade processing and model construction.
关键词
建筑物立面结构/点云分割/三维线段提取/法向量提取/点云降采样Key words
facade structure of building/point cloud segmentation/3D line segment extraction/normal vector extraction/downsampling of point cloud引用本文复制引用
基金项目
江西省教育厅科学技术研究项目(GJJ2200803)
出版年
2024
NETL
NSTL
万方数据