计算机应用研究 Application Research of Computers ISSN 1001-3695,CN 51-1196/TP 点的局部 几何特征，基于重叠分数和点特征的显著性保留重叠关键点。最后，利用重叠关键点的几何信息和空间信息构建混 合特征矩阵，计算矩阵的匹配相似度，采取加权奇异值分解运算得到配准结果。实验结果表明，该方法具有较强的 泛化能力，能在保证配准效率的同时，显著提升点云配准精度。 关键词：机器视觉；点云配准；重叠区域；混合特征 中图分类号：TP391 doi: .1001- Point cloud registration algorithm based on mixed-features sampling for overlapping domain Hu Jianghao, Wang Feng† (School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China) Abstract: Aiming at the problems of low efficiency and large error in the registration of two partially overlapped point clouds, this paper proposed a point cloud registration algorithm based on the mixed-features sampling for overlapping domain. First, it used coding and feature interaction predicted the overlap score of each point to obtain richer point cloud features. Second, it extracted the local geometric features of overlapping points and retained the overlapping key points based on overlapping scores and the significance of point features. Finally, it used the geometric information an
