危双丰, 刘明蕾, 赵江洪, 黄帅. 利用点云检测室内导航元素的方法综述[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2003-2011. DOI: 10.13203/j.whugis20180144
引用本文: 危双丰, 刘明蕾, 赵江洪, 黄帅. 利用点云检测室内导航元素的方法综述[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2003-2011. DOI: 10.13203/j.whugis20180144
WEI Shuangfeng, LIU Minglei, ZHAO Jianghong, HUANG Shuai. A Survey of Methods for Detecting Indoor Navigation Elements from Point Clouds[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2003-2011. DOI: 10.13203/j.whugis20180144
Citation: WEI Shuangfeng, LIU Minglei, ZHAO Jianghong, HUANG Shuai. A Survey of Methods for Detecting Indoor Navigation Elements from Point Clouds[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2003-2011. DOI: 10.13203/j.whugis20180144

利用点云检测室内导航元素的方法综述

A Survey of Methods for Detecting Indoor Navigation Elements from Point Clouds

  • 摘要: 随着大型公共设施的普及和人们室内活动的增多,人们对构建室内精细化导航模型的需求日渐迫切。近年来飞速发展的三维激光扫描、摄影测量、计算机视觉等技术,能够快速高效地获取高精度室内点云数据,为室内精细化导航提供丰富的数据源。如何从海量杂乱的点云中提取出可用于室内导航路径规划的室内导航元素如房间、门窗、楼梯、走廊等,成为了研究的热点和难点。因此,从基于点云的室内导航元素提取所面临的问题出发,综述和评价了近年来各种导航元素提取的相关理论和算法,并针对其各自优缺点,提出利用几何方法与统计方法相结合实现室内导航元素检测和导航网络构建的新思路。

     

    Abstract: With the popularity of large-scale public facilities, and increasing human indoor activities, people get an urgent demand for indoor refined navigation models. In recent years, 3D reconstruction technology such as 3D laser scanning, photogrammetry and computer vision grows fast. They can acquire high-precision data quickly and efficiently, and consequently provide rich data source for indoor refined navigation. However, the methods to extract indoor navigation elements available for indoor pathfinding like rooms, doors and windows, stairs, corridors have been one of difficult and attractive fields. For this purpose, aiming at the problems in indoor navigation, this paper summarizes and evaluates various algorithms and theories for indoor navigation elements extraction from point cloud, and proposes a new idea for indoor navigation elements extraction and navigation network generation from point cloud which combines geometric and statistical methods on the basis of summarized advantages and disadvantages, and thus offers the reference for the same trade or occupation.

     

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