利用图割算法进行城市密集点云表面模型重建
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摘要
利用倾斜影像获得的密集点云来构建表面模型是基于倾斜影像进行三维重建的核心之一。本文针对现行密集点云表面模型重建存在的建模效率低、表面选取不真实等问题,提出了一种基于图割算法的城市密集点云表面模型重建方法。利用该方法重建城市密集点云表面模型,首先通过预处理软件对无人机倾斜影像进行空中三角测量,并利用空中三角测量的解算结果生成密集点云;然后对密集点云添加相应的边,同时对三维点云根据距离进行选取合并;最后根据三维点云形成的四面体和三角面建立图割问题,并通过求解图割问题来求取最优的密集点云表面模型。为证明这种方法的可行性和有效性,使用城市地区的无人机倾斜影像数据进行城市密集点云表面模型重建,试验结果表明,该方法具有可行性好、建模效果好、处理速度快等优势。
The construction of surface model by using dense point cloud obtained from oblique image is one of the core of 3D reconstruction based on oblique images.For the problems of low modeling efficiency and unreal surface selection in the current dense point cloud surface model reconstruction,a new method of urban dense point cloud surface model reconstruction based on graph-cuts algorithm is proposed.This method is used to reconstruct the surface model of the urban dense point cloud.First,the aerial triangulation of the unmanned aerial vehicle(UAV) image is done by the preprocessing software,and the dense point cloud is generated by the results of the aerial triangulation,then the corresponding edges are added to the dense point cloud,and the 3D point clouds are selected and merged according to the distance.Finally,a graph-cuts problem is established based on the tetrahedron and triangulation formed by the 3D point cloud,and an optimal dense point cloud surface model is obtained by solving the graph-cuts problem.In order to prove the feasibility and effectiveness of this method,the UAV image data in urban areas is used to reconstruct the urban dense point cloud surface model,and the experimental results show that the method has the advantages of good feasibility,good modeling effect,fast processing speed and so on.
The construction of surface model by using dense point cloud obtained from oblique image is one of the core of 3D reconstruction based on oblique images.For the problems of low modeling efficiency and unreal surface selection in the current dense point cloud surface model reconstruction,a new method of urban dense point cloud surface model reconstruction based on graph-cuts algorithm is proposed.This method is used to reconstruct the surface model of the urban dense point cloud.First,the aerial triangulation of the unmanned aerial vehicle(UAV) image is done by the preprocessing software,and the dense point cloud is generated by the results of the aerial triangulation,then the corresponding edges are added to the dense point cloud,and the 3D point clouds are selected and merged according to the distance.Finally,a graph-cuts problem is established based on the tetrahedron and triangulation formed by the 3D point cloud,and an optimal dense point cloud surface model is obtained by solving the graph-cuts problem.In order to prove the feasibility and effectiveness of this method,the UAV image data in urban areas is used to reconstruct the urban dense point cloud surface model,and the experimental results show that the method has the advantages of good feasibility,good modeling effect,fast processing speed and so on.
引文
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[15]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.
[16]朱英浩,张祖勋,张剑清.顾及地形的城市三维可视化方法研究[J].武汉测绘科技大学学报,1998,23(3):199-203.
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[2]詹总谦,林元培,艾海滨.基于3ds Max二次开发的建筑物快速三维重建[J].测绘通报,2016(11):22-25.
[3]王迅.近景摄影与3D MAX在3维建模中的应用[J].测绘与空间地理信息,2010,33(2):121-122.
[4]娄启业,程效军,谭凯.基于Auto CAD和3DMax的建筑物三维建模[J].工程勘察,2013,41(11):71-74.
[5]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):1509-1516.
[6]马东岭,王晓坤,李广云.一种基于高度差异的点云数据分类方法[J].测绘通报,2018(6):46-49.
[7]ROCCHINI C,CIGNONI P,GANOVELLI F,et al.Marching intersections:an efficient resampling algorithm for surface management[C]∥International Conference on Shape Modeling&Applications.[S.l.]:IEEE,2001:296.
[8]AMENTA N,CHOI S,KOLLURI R K.The power crust[C]∥ACM Symposium on Solid Modeling&Applications.[S.l.]:ACM,2001:249-266.
[9]GROSS M.Algebraic point set surfaces[C]∥ACM SIGGR-APH.[S.l.]:ACM,2007.
[10]KOLLURI R.Provably good moving least squares[J].ACM Transactions on Algorithms,2008,4(2):1-25.
[11]HOPPE H,DEROSE T,DUCHAMP T,et al.Surface reconstruction from unorganized points[J].ACMSiggraph Computer Graphics,1992,26(26):71-78.
[12]邓德标,方源敏,陈杰.基于三角形法向量的离散点三维构网方法[J].遥感信息,2013,28(1):11-15.
[13]王宏志,刘江,张世荣.离散数据点集的3D三角划分算法研究[J].工具技术,2008,42(4):85-89.
[14]张帆,黄先锋,李德仁.基于球面投影的单站地面激光扫描点云构网方法[J].测绘学报,2009,38(1):48-54.
[15]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.
[16]朱英浩,张祖勋,张剑清.顾及地形的城市三维可视化方法研究[J].武汉测绘科技大学学报,1998,23(3):199-203.
[17]朱程辉,任冉冉.一种基于图割理论的快速立体匹配算法[J].微型机与应用,2010,29(10):35-38.
[18]MA D,LI G,CUI J,et al.Research on redundant data reduction algorithm of laser scanning point cloud based on curvature and norma[J].Boletin Tecnico/technical Bulletin,2017,55(6):272-278.
[19]MA D.Precise processing of point cloud data in omnidirectional scanning based on three-dimensional laser sensor[J].Journal of Nanoelectronics&Optoelectronics,2017,12(9):940-944.