直线簇约束下的地面LiDAR点云配准方法
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摘要
高精度的地面LiDAR点云配准是空间目标三维表面拓扑重建的关键,针对待配准LiDAR点云和基准LiDAR点云存在位置、姿态和比例缩放差异的问题,提出了基于直线簇的地面LiDAR点云配准方法。首先,根据直线间相交、平行和异面的拓扑关系,分别对待配准和基准LiDAR点云的直线进行聚簇,构建直线簇;然后,分别将同名直线用Plücker坐标表示,通过待配准LiDAR点云的直线簇在空间中的螺旋缩放运动,使其与基准LiDAR点云的直线簇比例尺一致,且同名Plücker直线重合,构建基于直线簇的共线条件方程,实现了比例因子和相对位姿一体化解算。实验结果表明,直线簇的螺旋缩放增强了配准方程的几何约束性,提高了抗噪声能力,实现了高精度的地面LiDAR点云配准。
The high precision terrestrial LiDAR point clouds registration is the key to ensure 3D topological reconstruction of spatial objects.The reference LiDAR point clouds and the LiDAR point clouds to be registered have the issue of different position,attitude and scale.A registration method based on line cluster is proposed.Firstly,line cluster of the reference LiDAR point clouds and the LiDAR point clouds to be registered is respectively established according to the topological relation of lines.Then conjugate lines of point clouds are represented in Plücke coordinate.Through the spiral zooming motion of line cluster of the LiDAR point clouds to be registered,finally the scale of the two LiDAR point clouds is the same and the conjugate Plücke lines coincide with each other.The collinearity equations based on line cluster can solve the scale factor and the relative position and attitude simultaneously with high precision.The experimental results show that,the spiral and scaling of the line cluster enhances the geometric constraints of the registration equation,improves the ability of anti-noise,and realizes the high precision of terrestrial LiDAR point clouds registration.
The high precision terrestrial LiDAR point clouds registration is the key to ensure 3D topological reconstruction of spatial objects.The reference LiDAR point clouds and the LiDAR point clouds to be registered have the issue of different position,attitude and scale.A registration method based on line cluster is proposed.Firstly,line cluster of the reference LiDAR point clouds and the LiDAR point clouds to be registered is respectively established according to the topological relation of lines.Then conjugate lines of point clouds are represented in Plücke coordinate.Through the spiral zooming motion of line cluster of the LiDAR point clouds to be registered,finally the scale of the two LiDAR point clouds is the same and the conjugate Plücke lines coincide with each other.The collinearity equations based on line cluster can solve the scale factor and the relative position and attitude simultaneously with high precision.The experimental results show that,the spiral and scaling of the line cluster enhances the geometric constraints of the registration equation,improves the ability of anti-noise,and realizes the high precision of terrestrial LiDAR point clouds registration.
引文
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[10]Zhen Dehua,Yue Dongjie,Yue Jianping.Geometric Feature Constraint Based Algorithm for Building Scanning Point Cloud Registration[J].Acta Geodaetica et Cartographica Sinica,2008,37(4):464-468(郑德华,岳东杰,岳建平.基于几何特征约束的建筑物点云配准算法[J].测绘学报,2008,37(4):464-468
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[14]Sheng Qinghong,Chen Shuwen,Fei Lijia,et al.Registration of Aerial Image with Airborne LiDAR Data Based on Plücke Line[J].Acta Geodaetica et Cartographica Sinica,2015,44(7):761-767(盛庆红,陈姝文,费利佳,等.基于Plücke直线的机载LiDAR点云与航空影像的配准[J].测绘学报,2015,44(7):761-767)
[15]Lasenby J,Fitzgerald W J,Lasenby A N,et al.New Geometric Methods for Computer Vision:An Application to Structure and Motion Estimation[J].International Journal of Computer Vision,1998,26(3):191-213
[2]Wang Yongbo,Yang Huachao,Liu Yanhua,et al.Linear-Feature-Constrained Registration of LiDAR Point Cloud via Quaternion[J].Geomatics and Information Science of Wuhan University,2013,38(9):1 057-1 063(王永波,杨化超,刘燕华,等.线状特征约束下基于四元数描述的LiDAR点云配准方法[J].武汉大学学报·信息科学版,2013,38(9):1 057-1 063)
[3]Yao Jili,Jia Xiangyang,Ma Ning,et al.Overall Orientation Adjustment Model of Terrestrial Laser Scanning Multi-station Point Clouds[J].Acta Geodaetica et Cartographica Sinica,2014,43(8):835-841(姚吉利,贾象阳,马宁,等.地面激光扫描多站点云整体定向平差模型[J].测绘学报,2014,43(8):835-841)
[4]Wang Yanmin,Shi Hongbin.An Automatic Registration Method for Building Point Clouds Based on3D Line Features[J].Bulletin of Surveying and Mapping,2014(9):23-25(王晏民,石宏斌.应用三维线特征自动配准建筑物点云数据[J].测绘通报,2014(9):23-25)
[5]Jen J J,Tzu Y C.Registration of Ground-Based LiDAR Point Clouds by Means of 3D Line Features[J].Journal of the Chinese Institute of Engineers,2008,31(6):1 031-1 045
[6]Wang Yongbo,Yang Huachao,Liu Yanhua,et al.A Dual Quaternion-Based,Closed-Form Pairwise Registration Algorithm for Point Clouds[J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,94(4):63-69
[7]Kou Yuan,Xu Jingzhong.Algorithm forRemote Sensing Images Matching Based on the Structure Characteristics[J].Journal of Image and Graphics,2013,18(5):565-573(寇媛,徐景中.基于结构特征的遥感影像匹配[J].中国图象图形学报,2013,18(5):565-573)
[8]Guan Y,Zhang H.Initial Registration for Point Clouds Based on Linear Features[C].The 4th International Symposium on Knowledge Acquisition and Modeling,Sanya,China,2011
[9]Xu Jingzhong,Kou Yuan,Yuan Fang,et al.AutoRegistration of Aerial Imagery and Airborne LiDAR Data Based on Structure Feature[J].Infrared and Laser Engineering,2013(12):42-52(徐景中,寇媛,袁芳,等.基于结构特征的机载LiDAR数据与航空影像自动配准[J].红外与激光工程,2013(12):42-52)
[10]Zhen Dehua,Yue Dongjie,Yue Jianping.Geometric Feature Constraint Based Algorithm for Building Scanning Point Cloud Registration[J].Acta Geodaetica et Cartographica Sinica,2008,37(4):464-468(郑德华,岳东杰,岳建平.基于几何特征约束的建筑物点云配准算法[J].测绘学报,2008,37(4):464-468
[11]Funda J,Taylor R H,Paul R P.On Homogeneous Transforms,Quaternions,and Computational Efficiency[J].IEEE Transactions on Robotics and Automation,1990,1(6):382-388
[12]Ronda J I,Gallego G,Valdes A.Camera Autocalibration Using Plücke Coordinates[C].IEEE International Conference on Image Processing,Genova,2005
[13]Sariyildiz E,Temeltas H.Solution of Inverse Kinematic Problem for Serial Robot Using Dual Quaterninons and PlückeCoordinates[C].ASME International Conference on Advanced Intelligent Mechatronics,Singapore,2009
[14]Sheng Qinghong,Chen Shuwen,Fei Lijia,et al.Registration of Aerial Image with Airborne LiDAR Data Based on Plücke Line[J].Acta Geodaetica et Cartographica Sinica,2015,44(7):761-767(盛庆红,陈姝文,费利佳,等.基于Plücke直线的机载LiDAR点云与航空影像的配准[J].测绘学报,2015,44(7):761-767)
[15]Lasenby J,Fitzgerald W J,Lasenby A N,et al.New Geometric Methods for Computer Vision:An Application to Structure and Motion Estimation[J].International Journal of Computer Vision,1998,26(3):191-213