| 利用点云检测室内导航元素的方法综述 |
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| 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. |
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| 作者姓名： | 危双丰 刘明蕾 赵江洪 黄帅 |
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| 作者单位： | 1.北京建筑大学测绘与城市空间信息学院, 北京, 102616 |
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| 基金项目： | 北京建筑大学市属高校基本科研业务费专项资金X18229北京建筑大学研究生创新项目PG2018066国家自然科学基金41601409北京市自然科学基金8172016城市空间信息工程北京市重点实验室开放研究基金2018210 |
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| 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。
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| 关 键 词： | 点云 室内导航元素 三维重建 点云分类 语义标注 |
| 收稿时间： | 2018-09-03 |
A Survey of Methods for Detecting Indoor Navigation Elements from Point Clouds |
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| Affiliation: | 1.School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102616, China2.Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, Beijing 102616, China3.Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 102616, China4.Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health Monitoring, Beijing 102616, China |
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| 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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