重庆理工大学学报(自然科学) ›› 2023, Vol. 37 ›› Issue (4): 182-191.

• 智能技术 • 上一篇    下一篇

一种基于球邻域空间体素切分的特征描述方法

张 健,杨 炯   

  1. 郑州大学 机械与动力工程学院,郑州 45000
  • 出版日期:2023-05-06 发布日期:2023-05-06
  • 作者简介:张健,男,硕士研究生,主要从事 3D视觉、计算机视觉和图形学研究,Email:kincheung@126.com;通信作者 杨 炯,男,讲师,主要从事机械设计、计算机图形学研究,Email:jiong_yang@foxmail.com。

A feature description method based on voxel partition in spherical neighborhood space

  • Online:2023-05-06 Published:2023-05-06

摘要: 针对复杂干扰场景中 3D特征描述子描述性和稳定性低的问题,提出了一种基于球 邻域空间体素切分的特征描述方法。此方法由一种稳定的局部参考坐标系 LRF(localreference frame)和一种基于体素表达的特征描述子组成。对于 LRF,以加权的协方差矩阵计算 Z轴,以 加权的点云投影向量之和作为 X轴,Y轴由二轴的叉乘得到。对于特征描述子,对球邻域进行 空间切分,通过判断每个空间体素内是否含有点来确定体素标签值,最后按照体素索引编码得 到该关键点的特征信息。实验证明:该方法相比于其他描述子,对噪声、点云表面分布不均、散 乱遮挡等干扰具有优异的性能,并且具有良好的泛化性,配准实验进一步验证了该描述子的有 效性。

关键词: :LRF, 体素切分, 特征提取, 特征描述

Abstract: Aiming at low description and stability of 3D feature descriptors in complex interference scenes, this paper proposes a feature description method based on voxel partition in spherical neighborhood space. This method consists of a stable local reference frame (LRF) and a feature descriptor based on voxel expression. For LRF, the Z-axis is calculated through the weighted covariance matrix, the sum of the weighted point cloud projection vectors is taken as the X-axis, and the Y-axis is obtained by the cross multiplication of the two axes. For feature descriptors, the spherical neighborhood is spatially divided, and the voxel label value is determined by judging whether there are points in each spatial voxel. Finally, the feature information of the key points is encoded according to the voxel index. The experiments show that, compared with other descriptors, this method has excellent performance against noise, uneven distribution of point cloud surface, scattered occlusion and other interference, and has good generalization. The registration experiments further verify the effectiveness of this descriptor.

中图分类号: 

  • TP391.4