Research on 3D Point Cloud Segmentation Algorithm in PCL Environment

ZHOU Bing-nan; MIN Hua-song; KANG Ya-wen

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Research on 3D Point Cloud Segmentation Algorithm in PCL Environment

更新时间：2026-09-04

- Research on 3D Point Cloud Segmentation Algorithm in PCL Environment
- Vol. 35, Issue 6, Pages: 101-105(2018)
- 作者机构：
  
  武汉科技大学冶金自动化与检测技术教育部工程研究中心机构,湖北,武汉,430081
- 作者简介：
- 基金信息：
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- Published：2018
- 稿件说明：
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周炳南, 闵华松, 康雅文. PCL环境下的3D点云分割算法研究[J]. 微电子学与计算机, 2018, 35(6): 101-105.

ZHOU Bing-nan, MIN Hua-song, KANG Ya-wen. Research on 3D Point Cloud Segmentation Algorithm in PCL Environment[J]. 2018, 35(6): 101-105.
周炳南, 闵华松, 康雅文. PCL环境下的3D点云分割算法研究[J]. 微电子学与计算机, 2018, 35(6): 101-105. DOI：

ZHOU Bing-nan, MIN Hua-song, KANG Ya-wen. Research on 3D Point Cloud Segmentation Algorithm in PCL Environment[J]. 2018, 35(6): 101-105. DOI：

摘要

本文在点云库的基础上

比较经典的欧式距离分割算法、区域生长分割算法和最新的SegmenterLight分割算法并对影响分割性能的预处理算法做出对比分析.根据得到的实验结果

本文对取得最佳的分割性能的预处理算法给出建议.

Abstract

This paper compares classic Euclidean distance segmentation algorithm and the regional growth segmentation algorithm with state-of-art SegmenterLight segmentation algorithm

and makes a comparative analysis of the preprocessing algorithm that affects the segmentation performance. Based on the experimental results

we give suggestions for the preprocessing algorithm achieving the best segmentation performance.

关键词

Keywords

references

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Shamir A. Segmentation and shape extraction of 3D boundary meshes(state of the art report), [C] //In Eurographice, Vienna, Austria, 2006: 137-149.

ückermann A, Haschke R, Ritter H. Realtime 3D segmentation for human-robot interaction[C]. Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE, 2013: 2136-2143.

Choi C, Christensen H I. RGB-D object tracking: A particle filter approach on GPU[C]. Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE, 2013: 1084-1091.

Kinect, 2016.[Online].Available.: http://www.xbox.com/en-US/xboxone/accessories/kinect-for-xbox-one.

李波, 李智, 王祥凤.基于多角度点云数据的快速配准方法[J].微电子学与计算机, 2017, 34(2): 123-127. DOI: 123

朱晓鑫, 谢翔, 李国林.一种大场景有序点云的快速, 准确分割方法[J].微电子学与计算机, 2016, 33(11): 45-49. DOI: 45

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