基于邻域表面形变信息加权的点云配准 下载: 717次
李新春, 闫振宇, 林森. 基于邻域表面形变信息加权的点云配准[J]. 激光与光电子学进展, 2020, 57(14): 141102.
Xinchun Li, Zhenyu Yan, Sen Lin. Point Cloud Registration Based on Weighting Information of Neighborhood Surface Deformation[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141102.
[1] 伍龙华, 黄惠. 点云驱动的计算机图形学综述[J]. 计算机辅助设计与图形学学报, 2015, 27(8): 1341-1353.
Wu L H, Huang H. Survey on points-driven computer graphics[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(8): 1341-1353.
[2] Besl P J. McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(2): 239-256.
[3] LiuB, Gao XH, Liu HD, et al. A fast weighted registration method of 3D point cloud based on curvature feature[C]∥Proceedings of the 3rd International Conference on Multimedia and Image Processing-ICMIP 2018, March 16-18, 2018, Guiyang, China. New York: ACM, 2018: 83- 87.
[4] 张彬, 熊传兵. 基于体素下采样和关键点提取的点云自动配准[J]. 激光与光电子学进展, 2020, 57(4): 041008.
[5] 马忠玲, 周明全, 耿国华, 等. 一种基于曲率的点云自动配准算法[J]. 计算机应用研究, 2015, 32(6): 1878-1880, 1887.
Ma Z L, Zhou M Q, Geng G H, et al. Automatic registration algorithm for scattered point clouds based on curvature feature[J]. Application Research of Computers, 2015, 32(6): 1878-1880, 1887.
[6] 王帅, 孙华燕, 郭惠超. 适用于激光点云配准的重叠区域提取方法[J]. 红外与激光工程, 2017, 46(s1): s126002.
Wang S, Sun H Y, Guo H C. Overlapping region extraction method for laser point clouds registration[J]. Infrared and Laser Engineering, 2017, 46(s1): s126002.
[7] TombariF, Salti S, di Stefano L. Unique signatures of histograms for local surface description[M] ∥Daniilidis K, Maragos P, Paragios N. Computer vision-ECCV 2010. Lecture notes in computer science. Berlin: Springer, 2010, 6313: 356- 369.
[8] Rusu RB, BlodowN, BeetzM. Fast point feature histograms (FPFH) for 3D registration[C]∥2009 IEEE International Conference on Robotics and Automation, May 12-17, 2009, Kobe, Japan. New York: IEEE, 2009: 3212- 3217.
[9] 曾繁轩, 李亮, 刁鑫鹏. 基于曲率特征的迭代最近点算法配准研究[J]. 激光与光电子学进展, 2017, 54(1): 011003.
[10] 张哲, 许宏丽, 尹辉. 一种基于关键点选择的快速点云配准算法[J]. 激光与光电子学进展, 2017, 54(12): 121002.
[11] He Y, Liang B, Yang J, et al. Aniterative closest points algorithm for registration of 3D laser scanner point clouds with geometric features[J]. Sensors, 2017, 17(8): 1862.
[12] ElbazG, AvrahamT, FischerA. 3D point cloud registration for localization using a deep neural network auto-encoder[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 2472- 2481.
[13] Jauer P, Kuhlemann I, Bruder R, et al. Efficient registration of high-resolution feature enhanced point clouds[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 41(5): 1102-1115.
[14] 陆军, 范哲君, 王婉佳. 点邻域信息加权的点云快速拼接算法[J]. 计算机辅助设计与图形学学报, 2019, 31(7): 1238-1246.
Lu J, Fan Z J, Wang W J. Fast point cloud splicing algorithm based on weighted neighborhood information of points[J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(7): 1238-1246.
[15] 葛宝臻, 周天宇, 陈雷, 等. 基于改进ISS特征点与人工蜂群算法的点云拼接方法[J]. 天津大学学报, 2016, 49(12): 1296-1302.
Ge B Z, Zhou T Y, Chen L, et al. Point clouds registration algorithm based on improved ISS feature points and artificial bee colony algorithm[J]. Journal of Tianjin University, 2016, 49(12): 1296-1302.
[16] 陶海跻, 达飞鹏. 一种基于法向量的点云自动配准方法[J]. 中国激光, 2013, 40(8): 0809001.
[17] 袁志聪, 鲁铁定, 邓小渊. 点云的刚体运动参数估计方法的比较[J]. 测绘工程, 2018, 27(4): 34-40.
Yuan Z C, Lu T D, Deng X Y. Comparison of parameter estimation methods for rigid motion of point cloud[J]. Engineering of Surveying and Mapping, 2018, 27(4): 34-40.
[18] 唐志荣, 蒋悦, 苗长伟, 等. 基于因子分析法的三维点云配准算法[J]. 激光与光电子学进展, 2019, 56(19): 191503.
[19] 陈旭, 何炳蔚. 一种基于校正点云主成分坐标系的快速全局配准算法[J]. 激光与光电子学进展, 2018, 55(6): 061003.
[20] 李仁忠, 杨曼, 田瑜, 等. 基于ISS特征点结合改进ICP的点云配准算法[J]. 激光与光电子学进展, 2017, 54(11): 111503.
[21] 王勇, 邹辉, 何养明, 等. 多分辨率配准点的ICP算法[J]. 小型微型计算机系统, 2018, 39(3): 406-410.
Wang Y, Zou H, He Y M, et al. ICP algorithm based on multi-resolution registration point[J]. Journal of Chinese Computer Systems, 2018, 39(3): 406-410.
李新春, 闫振宇, 林森. 基于邻域表面形变信息加权的点云配准[J]. 激光与光电子学进展, 2020, 57(14): 141102. Xinchun Li, Zhenyu Yan, Sen Lin. Point Cloud Registration Based on Weighting Information of Neighborhood Surface Deformation[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141102.