利用点云检测室内导航元素的方法综述
|
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。
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, 3 D reconstruction technology such as 3 D 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.
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, 3 D reconstruction technology such as 3 D 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.
引文
[1] Klepeis N E, Ott W C, Robinson W, et al. A Resource for Assessing Exposure to Environmental Pollutants[J]. Expo Anal Environ Epidemiol, 2001,11(3): 231-252
[2] Xu Jing. Research on Path Planning of the Indoor Mobile Navigation System[D].Changchun: Changchun University of Science and Technology,2009 (徐静. 室内移动导航系统的路径规划方法研究[D].长春:长春理工大学, 2009)
[3] Schougaard K R, Gr⌀nbæk K, Scharling T. Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling[M]. Berlin, Heidelberg: Springer, 2012
[4] Zhu Qing, Hu Mingyuan, Xu Weiping, et al.3D Building Information Model for Facilitating Dynamic Analysis of Indoor Fire Emergency[J]. Geomatics and Information Science of Wuhan University,2014, 39(7):762-766(朱庆, 胡明远, 许伟平,等. 面向火灾动态疏散的三维建筑信息模型[J]. 武汉大学学报·信息科学版, 2014, 39(7):762-766)
[5] Yang Dejun. The Design and Implementation of the Indoor Positioning and Navigation System[D]. Beijing: Beijing University of Posts and Telecommunications, 2011(杨德君. 室内精确定位导航系统的设计与实现[D].北京:北京邮电大学, 2011)
[6] Ptrucean V, Armeni I, Nahangi M, et al. State of Research in Automatic As-Built Modelling[J]. Advanced Engineering Informatics, 2015, 29(2):162-171
[7] Lin Y H, Liu Y S, Gao G, et al. The IFC-Based Path Planning for 3D Indoor Spaces[J]. Advanced Engineering Informatics, 2013, 27(2):189-205
[8] Ullah B S, Rahman A A. A Three-Step Strategy for Generalization of 3D Building Models Based on CityGML Specifications[J].Geojournal, 2013,8 (6):1 013-1 020
[9] Nakagawa M. Panoramic Rendering-Based Polygon Extraction from Indoor Mobile LiDAR Data [C]. International Academic Conference of Geodatabase and LBS, Suzhou, China, 2014
[10] Qian Jinju, Yang Bisheng, Chen Chi, et al. Automatic Registration of Terrestrial LiDAR Points with Texture Images[J]. Journal of Geomatics, 2015, 40(3):18-20( 钱金菊, 杨必胜, 陈驰,等. 地面激光点云与纹理影像的自动配准[J]. 测绘地理信息, 2015, 40(3):18-20)
[11] Zeng Qihong. Airborne LiDAR Point Cloud Data Processing and 3D Building Reconstruction[D].Shanghai: Shanghai University,2009(曾齐红. 机载激光雷达点云数据处理与建筑物三维重建[D]. 上海:上海大学, 2009)
[12] Zeng L, Kang Z. Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, XLII-2/W7:431-437
[13] Gong Yuejian, Mao Wenbo, Bi Jiantao, et al.Three-Dimensional Reconstruction of Indoor Whole Elements Based on Mobile LiDAR Point Cloud Data[J].Engineering of Surving and Mapping, 2015,24(11):33-38(龚跃健, 毛文博, 毕建涛,等. 基于移动LiDAR点云数据的室内全要素三维重建[J]. 测绘工程, 2015,24(11):33-38)
[14] Hong Zhentian, Yang Bisheng, Dong Zhen, et al. Key Technology Research of Rapid Mapping Based on Ground-Laser Scanning[J]. Geomatics World, 2015,22(3):111-115(洪镇填, 杨必胜, 董震,等. 基于地面激光扫描的快速成图关键技术研究[J]. 地理信息世界, 2015,22(3):111-115)
[15] Zhang Ruiju, Zheng Shaokai, Yin Jianying. Buil- ding Facade Point Cloud Semantic Segmentation Method Research[J]. Urban Geotechnical Investigation & Surveying, 2017(5):22-25(张瑞菊, 郑少开, 尹建英. 建筑物立面点云语义分割方法研究[J]. 城市勘测, 2017(5):22-25)
[16] Kolarek M. CityGML[J]. Ekscentar, 2009(11):32-35
[17] Huang He,Wang Liu,Jiang Bin, et al.Precision Verification of 3D SLAM Backpacked Mobile Mapping Robot[J].Bulletin of Surveying and Mapping,2016(12):68-73(黄鹤, 王柳, 姜斌,等. 3D SLAM激光影像背包测绘机器人精度验证[J]. 测绘通报, 2016(12):68-73)
[18] Ma Liguang. Classification and Application of Terrestrial Laser Scanners[J].Geospatial Information, 2005, 3(3):60-62(马立广. 地面三维激光扫描仪的分类与应用[J]. 地理空间信息, 2005, 3(3):60-62)
[19] Nikoohemat S, Peter M, Elberink O, et al. Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds[J]. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, IV-2/W4:355-362
[20] Boulos M N K, Blanchard B J, Walker C, et al. Web GIS in Practice X: A Microsoft Kinect Natural User Interface for Google Earth Navigation[J]. International Journal of Health Geographics, 2011, 10(1): 45-54
[21] Liu J, Gong X, Liu J. Guided in Painting and Filtering for Kinect Depth Maps[C]. IEEE International Conference on Pattern Recognition, Tsukuba, Japan, 2012
[22] Wu Lei.3D Reconstruction of Indoor Scenes Based on Kinect[D]. Beijing: Institute of Technology, 2015(吴磊. 基于Kinect的室内场景三维重建[D]. 北京:北京理工大学, 2015)
[23] Lu Wei, Wei Fengyuan, Zhang Shuo, et al. Research on Method of Constructing the Indoor Road Network Model[J]. Journal of Navigation and Positioning, 2014,2(4):63-67(卢伟, 魏峰远, 张硕,等. 室内路网模型的构建方法研究与实现[J]. 导航定位学报, 2014,2(4):63-67)
[24] Barnea S, Filin S. Segmentation of Terrestrial Laser Scanning Data Using Geometry and Image Information[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 76(1):33-48
[25] Budroni A, Boehm J. Automated 3D Reconstruction of Interiors from Point Clouds[J]. International Journal of Architectural Computing, 2010, 8(1):55-73
[26] Huber A A. 3D Reconstruction of Interior Wall Surfaces Under Occlusion and Clutter [C]. IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, Hangzhou, China, 2011
[27] Sanchez V,Zakhor A. Planar 3D Modeling of Buil- ding Interiors from Point Cloud Data[C]. IEEE International Conference on Image Processing, Melbourne, Australia, 2013
[28] Oesau S, Lafarge F, Alliez P. Indoor Scene Reconstruction Using Feature Sensitive Primitive Extraction and Graph-Cut[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 90: 68-82
[29] Thomson C, Boehm J. Automatic Geometry Gene-ration from Point Clouds for BIM[J]. Remote Sen- sing, 2015(7): 11 753-11 775
[30] Ioannis A. Detection of Walls, Floors, and Ceilings in Point Cloud Data[C]. Construction Research Congress, San Juan, Puerto Rico, USA, 2016
[31] Ochmann S, Vock R, Wessel R, et al. Automatic Generation of Structural Building Descriptions from 3D Point Cloud Scans[C]. IEEE International Conference on Computer Graphics Theory and Applications, Berlin, Germany, 2015
[32] Schnabel R, Wahl R, Klein R. Efficient RANSAC for Point-Cloud Shape Detection[J]. Computer Graphics Forum, 2007,26(2):214-226
[33] Gao Guang, Ma Hongchao, Zhang Liang. Automatic Extraction of Building Roofs from LiDAR Data Using a Hybridized Method[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10):1 225-1 230(高广,马洪超, 张良. 利用合成算法从LiDAR数据提取屋顶面[J]. 武汉大学学报\5信息科学版, 2014, 39(10):1 225-1 230)
[34] Hu Wei, Lu Xiaoping, Li Cheng,et al. Extended RANSAC Algorithm for Building Roof Segmentation from LiDAR Data[J]. Bulletin of Surveying and Mapping, 2012(11):31-34(胡伟, 卢小平, 李珵,等. 基于改进RANSAC算法的屋顶激光点云面片分割方法[J]. 测绘通报, 2012(11):31-34)
[35] Li Yunfan,Tan Debao,Liu Rui,et al. An Improved RANSAC Algorithm for Building Point Clouds Segmentation in Consideration of Roof Structure[J]. Remote Sensing for Land and Resources,2017,29(4): 20-25(李云帆,谭德宝,刘瑞,等. 顾及建筑物屋顶结构的改进 RANSAC 点云分割算法[J]. 国土资源遥感,2017,29(4): 20-25)
[36] Li Zhen, Kang Zhizhong, Jia Fengman, et al. Research on Feature Fitting of Point Clouds Based on Bayes Sample Consensus Algorithm[J]. Science of Surveying and Mapping, 2015, 40(8):92-96(李珍, 康志忠, 贾丰蔓,等. 利用贝叶斯抽样一致性的点云特征面拟合[J]. 测绘科学, 2015, 40(8): 92-96)
[37] Díazvilariňo L, Boguslawski P, Khoshelham K, et al. Indoor Navigation from Point Clouds: 3D Mo- delling and Obstacle Detection[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, XLI-B4:275-281
[38] Lu Xueliang, Tong Xiaochong, Zhang Yongsheng, et al. An Improved Region-Growing Surface Triangulation Algorithm for Urban Dense Point Cloud[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6):832-837(卢学良, 童晓冲, 张永生,等. 城市密集点云的区域生长表面构网改进算法[J]. 武汉大学学报·信息科学版, 2016, 41(6):832-837)
[39] Staats B R, Diakité A A, Voûte R L, et al. Automatic Generation of Indoor Navigable Space Using a Point Cloud and Its Scanner Trajectory[C]. ISPRS Geospatial Week 2017, Wuhan, China, 2017
[40] Yan Li, Xie Hong, Hu Xiaobin, et al. A New Hybrid Plane Segmentation Approach of Point Cloud[J]. Geomatics and Information Science of Wuhan University, 2013, 38(5):517-521(闫利, 谢洪, 胡晓斌,等. 一种新的点云平面混合分割方法[J]. 武汉大学学报·信息科学版, 2013, 38(5):517-521)
[41] Turner E,Zakhor A. Watertight As-Built Architectural Floor Plans Generated from Laser Range Data[C]. The 2nd International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, Zurich, Switzerland, 2012
[42] Khoshelham K, Díazvilariňo L. 3D Modelling of Interior Spaces: Learning the Language of Indoor Architecture[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014, XL-5(5):321-326
[43] Okorn B, Xiong X, Akinci B, et al. Toward Automated Modeling of Floor Plans[C]. The 5th International Symposium 3D Data Processing, Visualization and Transmission, Paris, France, 2010
[44] Fichtner F W, Diakité A A, Zlatanova S, et al. Semantic Enrichment of Octree Structured Point Clouds for Multi-story 3D Pathfinding[J]. Tran- sactions in GIS, 2018, 22(1):233-248
[45] Oßwald S, Gutmann J S, Hornung A, et al. From 3D Point Clouds to Climbing Stairs: A Comparison of Plane Segmentation Approaches for Humanoids[C]. The 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Bled, Slovenia, 2011
[46] Eilering A, Yap V, Johnson J, et al. Identifying Support Surfaces of Climbable Structures from 3D Point Clouds[C]. IEEE International Conference on Robotics and Automation, Hong Kong, China, 2014
[47] Delmerico J A, Baran D, David P, et al. Ascending Stairway Modeling from Dense Depth Imagery for Traversability Analysis[C]. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013
[48] Bansal M, Matei B, Southall B, et al. A LiDAR Streaming Architecture for Mobile Robotics with Application to 3D Structure Characterization[C]. IEEE International Conference on Robotics and Automation, Shanghai, China, 2011
[49] Bansal M,Matei B. LiDAR-Based Door and Stair Detection from a Mobile Robot[C]. Unmanned Systems Technology XII, Orlando, FL, USA, 2010
[50] Ochmann S, Vock R, Wessel R. Towards the Extraction of Hierarchical Building Descriptions from 3D Indoor Scans[C]. Eurographics Workshop on 3D Object Retrieval Eurographics Association, Strasbourg, France, 2014
[51] Lu Xiushan, Huang Lei. Grid Method on Building Information Extraction Using Laser Scanning Data[J]. Geomatics and Information Science of Wuhan University, 2007, 32(10):852-855(卢秀山, 黄磊. 基于激光扫描数据的建筑物信息格网化提取方法[J]. 武汉大学学报·信息科学版, 2007, 32(10):852-855)
[52] Bogue R W. Machine Vision Theory, Algorithms, Practicalities[J].Assembly Automation, 2004, 25(3):58-59
[53] Armeni I, Sener O, Zamir A R, et al. 3D Semantic Parsing of Large-Scale Indoor Spaces[C]. Computer Vision and Pattern Recognition, Las Vegas, USA, 2016
[54] Armeni I. 3D Semantic Parsing of Large-Scale Indoor Spaces Supplementary Material[EB/OL]. http://cvgl.stanford.edu/papers/iro_cvpr16_supp.pdf, 2018
[55] Díazvilariňo L, Verbree E, Zlatanova S, et al. Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction[J]. Int Ann Photogramm Remote Sens Spatial Inf Sci, 2017,XLII-2/W7:345-352
[56] Díazvilariňo L, Khoshelham K, Martã-Nez-Sãn J, et al. 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds[J]. Sensors, 2015, 15(2): 3 491-3 512
[57] Yang B, Huang R, Dong Z. Two-Step Adaptive Extraction Method for Ground Points and Breaklines from Lidar Point Clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 119:373-389
[58] Yang Bisheng, Liang Fuxun, Huang Ronggang. Progress, Challenges and Perspectives of 3D LiDAR Point Cloud Processing[J]. Acta Geodaetica et Cartographica Sinica, 2017,46(10): 1 509-1 516(杨必胜, 梁福逊, 黄荣刚. 三维激光扫描点云数据处理研究进展、挑战与趋势[J]. 测绘学报, 2017,46(10): 1 509-1 516
[2] Xu Jing. Research on Path Planning of the Indoor Mobile Navigation System[D].Changchun: Changchun University of Science and Technology,2009 (徐静. 室内移动导航系统的路径规划方法研究[D].长春:长春理工大学, 2009)
[3] Schougaard K R, Gr⌀nbæk K, Scharling T. Indoor Pedestrian Navigation Based on Hybrid Route Planning and Location Modeling[M]. Berlin, Heidelberg: Springer, 2012
[4] Zhu Qing, Hu Mingyuan, Xu Weiping, et al.3D Building Information Model for Facilitating Dynamic Analysis of Indoor Fire Emergency[J]. Geomatics and Information Science of Wuhan University,2014, 39(7):762-766(朱庆, 胡明远, 许伟平,等. 面向火灾动态疏散的三维建筑信息模型[J]. 武汉大学学报·信息科学版, 2014, 39(7):762-766)
[5] Yang Dejun. The Design and Implementation of the Indoor Positioning and Navigation System[D]. Beijing: Beijing University of Posts and Telecommunications, 2011(杨德君. 室内精确定位导航系统的设计与实现[D].北京:北京邮电大学, 2011)
[6] Ptrucean V, Armeni I, Nahangi M, et al. State of Research in Automatic As-Built Modelling[J]. Advanced Engineering Informatics, 2015, 29(2):162-171
[7] Lin Y H, Liu Y S, Gao G, et al. The IFC-Based Path Planning for 3D Indoor Spaces[J]. Advanced Engineering Informatics, 2013, 27(2):189-205
[8] Ullah B S, Rahman A A. A Three-Step Strategy for Generalization of 3D Building Models Based on CityGML Specifications[J].Geojournal, 2013,8 (6):1 013-1 020
[9] Nakagawa M. Panoramic Rendering-Based Polygon Extraction from Indoor Mobile LiDAR Data [C]. International Academic Conference of Geodatabase and LBS, Suzhou, China, 2014
[10] Qian Jinju, Yang Bisheng, Chen Chi, et al. Automatic Registration of Terrestrial LiDAR Points with Texture Images[J]. Journal of Geomatics, 2015, 40(3):18-20( 钱金菊, 杨必胜, 陈驰,等. 地面激光点云与纹理影像的自动配准[J]. 测绘地理信息, 2015, 40(3):18-20)
[11] Zeng Qihong. Airborne LiDAR Point Cloud Data Processing and 3D Building Reconstruction[D].Shanghai: Shanghai University,2009(曾齐红. 机载激光雷达点云数据处理与建筑物三维重建[D]. 上海:上海大学, 2009)
[12] Zeng L, Kang Z. Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, XLII-2/W7:431-437
[13] Gong Yuejian, Mao Wenbo, Bi Jiantao, et al.Three-Dimensional Reconstruction of Indoor Whole Elements Based on Mobile LiDAR Point Cloud Data[J].Engineering of Surving and Mapping, 2015,24(11):33-38(龚跃健, 毛文博, 毕建涛,等. 基于移动LiDAR点云数据的室内全要素三维重建[J]. 测绘工程, 2015,24(11):33-38)
[14] Hong Zhentian, Yang Bisheng, Dong Zhen, et al. Key Technology Research of Rapid Mapping Based on Ground-Laser Scanning[J]. Geomatics World, 2015,22(3):111-115(洪镇填, 杨必胜, 董震,等. 基于地面激光扫描的快速成图关键技术研究[J]. 地理信息世界, 2015,22(3):111-115)
[15] Zhang Ruiju, Zheng Shaokai, Yin Jianying. Buil- ding Facade Point Cloud Semantic Segmentation Method Research[J]. Urban Geotechnical Investigation & Surveying, 2017(5):22-25(张瑞菊, 郑少开, 尹建英. 建筑物立面点云语义分割方法研究[J]. 城市勘测, 2017(5):22-25)
[16] Kolarek M. CityGML[J]. Ekscentar, 2009(11):32-35
[17] Huang He,Wang Liu,Jiang Bin, et al.Precision Verification of 3D SLAM Backpacked Mobile Mapping Robot[J].Bulletin of Surveying and Mapping,2016(12):68-73(黄鹤, 王柳, 姜斌,等. 3D SLAM激光影像背包测绘机器人精度验证[J]. 测绘通报, 2016(12):68-73)
[18] Ma Liguang. Classification and Application of Terrestrial Laser Scanners[J].Geospatial Information, 2005, 3(3):60-62(马立广. 地面三维激光扫描仪的分类与应用[J]. 地理空间信息, 2005, 3(3):60-62)
[19] Nikoohemat S, Peter M, Elberink O, et al. Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds[J]. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, IV-2/W4:355-362
[20] Boulos M N K, Blanchard B J, Walker C, et al. Web GIS in Practice X: A Microsoft Kinect Natural User Interface for Google Earth Navigation[J]. International Journal of Health Geographics, 2011, 10(1): 45-54
[21] Liu J, Gong X, Liu J. Guided in Painting and Filtering for Kinect Depth Maps[C]. IEEE International Conference on Pattern Recognition, Tsukuba, Japan, 2012
[22] Wu Lei.3D Reconstruction of Indoor Scenes Based on Kinect[D]. Beijing: Institute of Technology, 2015(吴磊. 基于Kinect的室内场景三维重建[D]. 北京:北京理工大学, 2015)
[23] Lu Wei, Wei Fengyuan, Zhang Shuo, et al. Research on Method of Constructing the Indoor Road Network Model[J]. Journal of Navigation and Positioning, 2014,2(4):63-67(卢伟, 魏峰远, 张硕,等. 室内路网模型的构建方法研究与实现[J]. 导航定位学报, 2014,2(4):63-67)
[24] Barnea S, Filin S. Segmentation of Terrestrial Laser Scanning Data Using Geometry and Image Information[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 76(1):33-48
[25] Budroni A, Boehm J. Automated 3D Reconstruction of Interiors from Point Clouds[J]. International Journal of Architectural Computing, 2010, 8(1):55-73
[26] Huber A A. 3D Reconstruction of Interior Wall Surfaces Under Occlusion and Clutter [C]. IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, Hangzhou, China, 2011
[27] Sanchez V,Zakhor A. Planar 3D Modeling of Buil- ding Interiors from Point Cloud Data[C]. IEEE International Conference on Image Processing, Melbourne, Australia, 2013
[28] Oesau S, Lafarge F, Alliez P. Indoor Scene Reconstruction Using Feature Sensitive Primitive Extraction and Graph-Cut[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 90: 68-82
[29] Thomson C, Boehm J. Automatic Geometry Gene-ration from Point Clouds for BIM[J]. Remote Sen- sing, 2015(7): 11 753-11 775
[30] Ioannis A. Detection of Walls, Floors, and Ceilings in Point Cloud Data[C]. Construction Research Congress, San Juan, Puerto Rico, USA, 2016
[31] Ochmann S, Vock R, Wessel R, et al. Automatic Generation of Structural Building Descriptions from 3D Point Cloud Scans[C]. IEEE International Conference on Computer Graphics Theory and Applications, Berlin, Germany, 2015
[32] Schnabel R, Wahl R, Klein R. Efficient RANSAC for Point-Cloud Shape Detection[J]. Computer Graphics Forum, 2007,26(2):214-226
[33] Gao Guang, Ma Hongchao, Zhang Liang. Automatic Extraction of Building Roofs from LiDAR Data Using a Hybridized Method[J]. Geomatics and Information Science of Wuhan University, 2014, 39(10):1 225-1 230(高广,马洪超, 张良. 利用合成算法从LiDAR数据提取屋顶面[J]. 武汉大学学报\5信息科学版, 2014, 39(10):1 225-1 230)
[34] Hu Wei, Lu Xiaoping, Li Cheng,et al. Extended RANSAC Algorithm for Building Roof Segmentation from LiDAR Data[J]. Bulletin of Surveying and Mapping, 2012(11):31-34(胡伟, 卢小平, 李珵,等. 基于改进RANSAC算法的屋顶激光点云面片分割方法[J]. 测绘通报, 2012(11):31-34)
[35] Li Yunfan,Tan Debao,Liu Rui,et al. An Improved RANSAC Algorithm for Building Point Clouds Segmentation in Consideration of Roof Structure[J]. Remote Sensing for Land and Resources,2017,29(4): 20-25(李云帆,谭德宝,刘瑞,等. 顾及建筑物屋顶结构的改进 RANSAC 点云分割算法[J]. 国土资源遥感,2017,29(4): 20-25)
[36] Li Zhen, Kang Zhizhong, Jia Fengman, et al. Research on Feature Fitting of Point Clouds Based on Bayes Sample Consensus Algorithm[J]. Science of Surveying and Mapping, 2015, 40(8):92-96(李珍, 康志忠, 贾丰蔓,等. 利用贝叶斯抽样一致性的点云特征面拟合[J]. 测绘科学, 2015, 40(8): 92-96)
[37] Díazvilariňo L, Boguslawski P, Khoshelham K, et al. Indoor Navigation from Point Clouds: 3D Mo- delling and Obstacle Detection[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, XLI-B4:275-281
[38] Lu Xueliang, Tong Xiaochong, Zhang Yongsheng, et al. An Improved Region-Growing Surface Triangulation Algorithm for Urban Dense Point Cloud[J]. Geomatics and Information Science of Wuhan University, 2016, 41(6):832-837(卢学良, 童晓冲, 张永生,等. 城市密集点云的区域生长表面构网改进算法[J]. 武汉大学学报·信息科学版, 2016, 41(6):832-837)
[39] Staats B R, Diakité A A, Voûte R L, et al. Automatic Generation of Indoor Navigable Space Using a Point Cloud and Its Scanner Trajectory[C]. ISPRS Geospatial Week 2017, Wuhan, China, 2017
[40] Yan Li, Xie Hong, Hu Xiaobin, et al. A New Hybrid Plane Segmentation Approach of Point Cloud[J]. Geomatics and Information Science of Wuhan University, 2013, 38(5):517-521(闫利, 谢洪, 胡晓斌,等. 一种新的点云平面混合分割方法[J]. 武汉大学学报·信息科学版, 2013, 38(5):517-521)
[41] Turner E,Zakhor A. Watertight As-Built Architectural Floor Plans Generated from Laser Range Data[C]. The 2nd International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, Zurich, Switzerland, 2012
[42] Khoshelham K, Díazvilariňo L. 3D Modelling of Interior Spaces: Learning the Language of Indoor Architecture[J]. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014, XL-5(5):321-326
[43] Okorn B, Xiong X, Akinci B, et al. Toward Automated Modeling of Floor Plans[C]. The 5th International Symposium 3D Data Processing, Visualization and Transmission, Paris, France, 2010
[44] Fichtner F W, Diakité A A, Zlatanova S, et al. Semantic Enrichment of Octree Structured Point Clouds for Multi-story 3D Pathfinding[J]. Tran- sactions in GIS, 2018, 22(1):233-248
[45] Oßwald S, Gutmann J S, Hornung A, et al. From 3D Point Clouds to Climbing Stairs: A Comparison of Plane Segmentation Approaches for Humanoids[C]. The 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Bled, Slovenia, 2011
[46] Eilering A, Yap V, Johnson J, et al. Identifying Support Surfaces of Climbable Structures from 3D Point Clouds[C]. IEEE International Conference on Robotics and Automation, Hong Kong, China, 2014
[47] Delmerico J A, Baran D, David P, et al. Ascending Stairway Modeling from Dense Depth Imagery for Traversability Analysis[C]. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013
[48] Bansal M, Matei B, Southall B, et al. A LiDAR Streaming Architecture for Mobile Robotics with Application to 3D Structure Characterization[C]. IEEE International Conference on Robotics and Automation, Shanghai, China, 2011
[49] Bansal M,Matei B. LiDAR-Based Door and Stair Detection from a Mobile Robot[C]. Unmanned Systems Technology XII, Orlando, FL, USA, 2010
[50] Ochmann S, Vock R, Wessel R. Towards the Extraction of Hierarchical Building Descriptions from 3D Indoor Scans[C]. Eurographics Workshop on 3D Object Retrieval Eurographics Association, Strasbourg, France, 2014
[51] Lu Xiushan, Huang Lei. Grid Method on Building Information Extraction Using Laser Scanning Data[J]. Geomatics and Information Science of Wuhan University, 2007, 32(10):852-855(卢秀山, 黄磊. 基于激光扫描数据的建筑物信息格网化提取方法[J]. 武汉大学学报·信息科学版, 2007, 32(10):852-855)
[52] Bogue R W. Machine Vision Theory, Algorithms, Practicalities[J].Assembly Automation, 2004, 25(3):58-59
[53] Armeni I, Sener O, Zamir A R, et al. 3D Semantic Parsing of Large-Scale Indoor Spaces[C]. Computer Vision and Pattern Recognition, Las Vegas, USA, 2016
[54] Armeni I. 3D Semantic Parsing of Large-Scale Indoor Spaces Supplementary Material[EB/OL]. http://cvgl.stanford.edu/papers/iro_cvpr16_supp.pdf, 2018
[55] Díazvilariňo L, Verbree E, Zlatanova S, et al. Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction[J]. Int Ann Photogramm Remote Sens Spatial Inf Sci, 2017,XLII-2/W7:345-352
[56] Díazvilariňo L, Khoshelham K, Martã-Nez-Sãn J, et al. 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds[J]. Sensors, 2015, 15(2): 3 491-3 512
[57] Yang B, Huang R, Dong Z. Two-Step Adaptive Extraction Method for Ground Points and Breaklines from Lidar Point Clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 119:373-389
[58] Yang Bisheng, Liang Fuxun, Huang Ronggang. Progress, Challenges and Perspectives of 3D LiDAR Point Cloud Processing[J]. Acta Geodaetica et Cartographica Sinica, 2017,46(10): 1 509-1 516(杨必胜, 梁福逊, 黄荣刚. 三维激光扫描点云数据处理研究进展、挑战与趋势[J]. 测绘学报, 2017,46(10): 1 509-1 516