基于点云内骨架的分割算法  

Segmentation Algorithm Based on Point Cloud Skeleton

作　　者：李仁忠[1] 刘哲闻 刘阳阳[1] Li Renzhong;Liu Zhewen;Liu Yangyang(School of Electronics and Information,Xi an Polytechnic University,Xi'an,Shaanxi,710048,China)

机构地区：[1]西安工程大学电子信息学院

出　　处：《激光与光电子学进展》2019年第22期82-89,共8页Laser & Optoelectronics Progress

基　　金：中国纺织工业联合会科技指导性项目（2017071）;陕西省高校科协青年人才托举计划（20180115）

摘　　要：提出一种有效的三维点云骨架分割的方法,分割后的结果可用于三维点云物体识别和分类。利用稳健性较强的L1-中心骨架算法对点云数据进行骨架提取,可得到一系列骨架点;利用基于八叉树的区域增长分割方法对已经得到的骨架点进行分割,选取法向量和残值作为判定标准;利用OpenGL库编程把分割出的各个部分进行骨架连线。对多种形状的点云数据(包括动物模型、植物模型、人体模型、字母模型)进行实验,该方法均得到较好的结果。This study presents an effective method for segmenting the skeleton of a three-dimensional point cloud.Segmentation results can be used in point cloud object recognition and classification.First,an L1-central skeleton algorithm with strong robustness is used to extract the skeleton of point cloud data,and a series of skeleton points is obtained.Then,the skeleton points are segmented by using the octree based region growing segmentation method.The selected criteria are normal vectors and residuals.Finally,OpenGL is used to connect the segmented parts.Numerous experiments are conducted with point cloud data of various shapes,such as animal,plant,human,and alphabetic models,and good results are obtained.

关 键 词：成像系统 三维点云 骨架提取 区域增长 点云分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]