Extracting outlined planar clusters of street facades from 3D point clouds

K. Hammoudi, F. Dornaika, B. Soheilian, N. Paparoditis
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引用次数: 14

Abstract

This paper presents an approach for extracting 3D outlined planar clusters of street facades. Terrestrial laser data are acquired using a Mobile Mapping System (MMS). Mapping of street facades is of great interest in various digital mapping and robotic research topics. After a filtering step of the 3D point cloud, the dominant hypothetical facade planes are detected using an adapted Progressive Probabilistic Hough Transform (PPHT). The corresponding planar clusters are extracted using a priori geometric knowledge of street. The clusters are horizontally and vertically delimited using heuristic approaches. The adapted PPHT allows the automatic extraction of georeferenced planar clusters of facades with a fine detection of dominant facade lines and a low computation time. The adopted approach has been tested on a set of point cloud acquired in the city of Paris under real conditions. Examples and experimental results show the efficiency and the potential of the proposed approach.
从三维点云中提取街道立面的轮廓平面集群
本文提出了一种提取街道立面三维轮廓平面簇的方法。地面激光数据是通过移动测绘系统(MMS)获取的。街道立面的测绘是各种数字测绘和机器人研究课题的重要内容。在对三维点云进行滤波后,使用自适应渐进概率霍夫变换(PPHT)检测主要的假设立面平面。使用先验的街道几何知识提取相应的平面聚类。使用启发式方法对集群进行水平和垂直划分。经过改进的PPHT可以自动提取立面的地理参考平面簇,对主要立面线进行精细检测,并且计算时间短。所采用的方法已在巴黎市实际条件下采集的一组点云上进行了测试。实例和实验结果表明了该方法的有效性和潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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