摘要
RGB-D相机作为一种常见的便携式三维数据采集工具被广泛使用于计算机图形学、计算机视觉等诸多领域,然而,由于设备的物理误差、光照干扰等因素,采集的三维点云中往往包含大尺度噪声,现有的点云配准方法处理这类数据时无法取得理想的配准结果,进而影响后续三维重建的质量.为了解决这一问题,提出一种鲁棒的基于RGB-D图像的刚性点云配准方法.首先,提出一种基于全变分和各向异性二阶算子的点法向估计方法,能够有效地去除点法向的噪声并且较好地保持尖锐和非线性光滑特征;其次,联合RGB图像的纹理信息和点云的几何信息设计了一种复合特征描述子,能够在包含噪声的点云上鲁棒地提取初始匹配点;最后,采用一种快速的全局配准方法计算待配准点云之间的刚性变换.在多组合成及真实点云数据上进行配准实验,并从视觉效果和配准误差2个方面对实验结果进行分析,分析结果表明,所提方法能够鲁棒地配准大噪声干扰的点云数据,验证了方法的有效性.
RGB-D camera,as a common portable 3D data acquisition tool,has been widely utilized in many fields,such as computer graphics,computer vision.However,the captured data is usually corrupted by large noise due to several reasons.For examples,the error of sensor,light interference,etc.The existing point cloud registration methods are incapable of generating desired registration results when processing such data corrupted by large noise,it will directly lead to the quality degradation of the subsequent 3D reconstruction.To tackle the problem,a robust point cloud registration method based on RGB-D images is introduced.First,a point normal estimation method based on a novel second-order operator is proposed,which can effectively remove the noise and simultaneously recover sharp features and nonlinear smooth regions.Then,a compound descriptor,used to robustly extract initial correspondences from noisy point clouds,is designed by combining both texture and geometry information obtained from RGB images and point clouds respectively.Finally,a fast optimization-based method is utilized to calculate the rigid transformation between a pair of point clouds.Intensive experiments on a variety of synthetic and raw point cloud data are conducted,and the experimental results are analyzed from points of the visual effect and the registration error.The analysis results demonstrate the effectiveness of the proposed method,especially in robustly registering point clouds corrupted by large noise.
作者
钟赛尚
李彦磊
刘郑
谢忠
陈建国
王伟明
刘秀平
Zhong Saishang;Li Yanlei;Liu Zheng;Xie Zhong;Chen Jianguo;Wang Weiming;Liu Xiuping(State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences,Wuhan 430074;School of Earth Resources,China University of Geosciences,Wuhan 430074;National Engineering Research Center of Geographic Information System,China University of Geosciences,Wuhan 430074;School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074;School of Mathematical Sciences,Dalian University of Technology,Dalian 116024)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2022年第1期25-35,共11页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(61702467,41671400,61702079)
开放基金(CY119R015)
国家重点研发计划(2017YFC0601500,2017YFC0601504,2018YFB0505500).
关键词
RGB-D相机
点云配准
点法向估计
全变分
各向异性二阶算子
RGB-D cameras
point cloud registration
point normal estimation
total variation
anisotropic second-order operator
作者简介
钟赛尚(1990-),男,博士,主要研究方向为点云配准、网格滤波;李彦磊(1997-),男,硕士研究生,主要研究方向为点云去噪;通信作者:刘郑(1983-),男,博士,副教授,硕士生导师,主要研究方向为数字几何处理、基于变分法的图像处理等,liu.zheng.jojo@gmail.com;谢忠(1968-),男,博士,教授,博士生导师,CCF会员,主要研究方向为遥感图像处理和分析;陈建国(1964-),男,博士,教授,博士生导师,主要研究方向为地球探测与信息技术、深部矿产资源定量评价;王伟明(1986-),男,博士,讲师,硕士生导师,主要研究方向为图像处理、3D打印;刘秀平(1964-),女,博士,教授,博士生导师,主要研究方向为多元样条处理、图像计算.
