A Point Cloud Fusion Method for Space Target 3D Laser Point Cloud and Visible Light Image Reconstruction Method

Abstract

In this paper, a high-precision spatial target lidar for 3D reconstruction of point cloud and visible light image 3D reconstruction point cloud fusion method is proposed. This fusion method uses the solved 3D reconstruction to invert the camera pose and 3D point cloud model centroid position optimization initial value selection. The registration accuracy and registration efficiency of the ICP algorithm are improved. At the same time, according to the characteristics of the two sets of point clouds, the Euclidean distance threshold is used to delete the noise points of the 3D point cloud edge, and the high-precision 3D reconstruction point with the scale information fusion is obtained. The simulation experiment of the spatial target simulation model shows that the fusion method can effectively improve the point cloud density, fill the reconstruction vulnerability, and improve the point cloud accuracy of the spatial target 3D reconstruction.

Keywords

space target / 3D reconstruction / laser radar / point cloud fusion / ICP

References

[1] XU Z , TU D , LIN L . Point cloud registration with 2D and 3D fusion information on mobile robot integrated vision system[C]// IEEE International Conference on Robotics & Biomimetics. [S. l. ]: IEEE, 2013.
[2] ZHANG Z, ZHAO R, LIU E, et al. A fusion method of 1D laser and vision based on depth estimation for pose estimation and reconstruction[J]. Robotics and Autonomous Systems,2019,116:181-191
[3] KE W, HONG L, GUO B, et al. A 6D-ICP approach for 3D reconstruction and motion estimate of unknown and non-cooperative target[C]//2016 Chinese Control and Decision Conference (CCDC) . Yinchuan, China: IEEE, 2016.
[4] 邵杰, 张爱武, 王书民, 等. 三维激光点云与CCD影像融合的研究[J]. 中国激光,2013,40(5):228-235
SHAO J, ZHANG A W, WANG S M, et al. Research on fusion of 3D laser point clouds and CCD image[J]. Chinese Journal of Lasers,2013,40(5):228-235
[5] 武殿梁, 黄海量, 丁玉成, 等. 基于遗传算法和最小二乘法的曲面匹配[J]. 航空学报,2002,23(3):285-288
WU D L, HUANG H L, DING Y C, et al. Surfaces matching algorithm based on genetic algorithm and least square criterion[J]. Acta Aeronautica et Astronautica Sinica,2002,23(3):285-288
[6] 武殿梁, 洪军, 丁玉成, 等. 测量点群与标准曲面的匹配算法研究[J]. 西安交通大学学报,2002,36(5):500-503
WU D L, HONG J, DING Y C, et al. Surfaces matching algorithm based on the least time criterion[J]. Journal of Xi'an Jiaotong University,2002,36(5):500-503
[7] 薛峰, 丁晓青. 基于形状匹配变形模型的三维人脸重构[J]. 电子学报,2006(10):154-157
XUE F, DING X Q. 3D reconstruction of human face based on shape match morphing model[J]. Acta Electronica Sinica,2006(10):154-157
[8] SZELISKI R , LAVALLEE S . Matching 3-D anatomical surfaces with non-rigid deformations usingoctree splines[C]//Proceedings of IEEE Workshop on Biomedical Image Analysis. Seattle, WA, USA: IEEE, 1994.
[9] CANUDAS D W C, LISCHINSKY P. Adaptive Friction Compensation with Partially Known Dynamic Friction Model[J]. International commission on radiation units and measurements,1997,11(1):65-80
[10] BESL P J. A method for registration of 3D shapes[J]. IEEE Trans on PAMI,1992,14(2):239-256
[11] MENQ C H, YAU H T, LAI G Y. Automated precision measurement of surface profile in CAD-directed inspection[J]. IEEE Transactions on Robotics & Automation,1992,8(2):268-278
[12] RUSINKIEWICZ S, LEVOY M. Efficient variants of the ICP algorithm[C]//In Proceedings Third International Conference on 3-D Digital Imaging and Modeling. [S. l.]: IEEE, 2001: 145-152.
[13] 张宗华, 彭翔, 胡小唐. 获取ICP匹配深度图像初值的研究[J]. 工程图学学报,2002(1):84-90
ZHANG Z H, PENG X, HU X T. The research on acquiring the initial value of registering range images by ICP[J]. Journal of Engineering Graphics,2002(1):84-90
[14] SINHA S . A multi-stage linear approach to structure from motion[M]. Berlin: Springer Berlin Heidelberg, 2012.
[15] SNAVELY N , SEITZ S M , SZELISKI R . Skeletal graphs for efficient structure from motion[C]// IEEE Conference on Computer Vision & Pattern Recognition. [S. l. ]: IEEE, 2008.
[16] CRANDALL D, OWENS A, SNAVELY N, et al. Discrete-continuous optimization for large-scale structure from motion[J]. IEEE Transactions on Software Engineering,2013,35(12):2841-2853
[17] GHERARDI R , FARENZENA M , FUSIELLO A . Improving the efficiency of hierarchical structure-and-motion[C]// The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010. San Francisco, CA, USA: IEEE, 2010.
[18] WU C , AGARWAL S , CURLESS B , et al. Multicore bundle adjustment[C]// Computer Vision & Pattern Recognition. [S. l. ]: IEEE, 2011.
[19] AGARWAL S , SNAVELY N , SEITZ S M , et al. Bundle adjustment in the large[C]// European Conference on Computer Vision. Berlin: Springer-Verlag, 2010.
[20] 钟莹, 张蒙. 基于改进ICP算法的点云自动配准技术[J]. 控制工程,2014,21(1):37-37
ZHONG Y, ZHANG M. Automatic registration technology of point cloud based on improved ICP algorithm[J]. Control Engineering of China,2014,21(1):37-37
[21] FURUKAWA Y, PONCE J. Accurate, dense, and robust multiview stereopsis[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on,2010,32(8):1362-1376
[22] TZSCHICHHOLZ T, BOGE T, SCHILLING K. Relative pose estimation of satellites using PMD-/CCD-sensor data fusion[J]. Acta Astronautica,2015,109:25-33