计算机与数字工程Issue(9)：2141-2144,4.DOI:10.3969/j.issn.1672-9722.2019.09.007
基于SDF及K-Means三维模型一致性分割算法∗
Consistency Segmentation Algorithm of 3D Model Set Based on SDF and K-Means
摘要
Abstract
In order to improve the accuracy of 3D model set consistency segmentation algorithm,an algorithm of 3D model set consistency segmentation based on SDF and K-Means is proposed. The SDF characteristics of each model in the model set is extract?ed. The significant feature points of the model are calculated which represent the segmentation parts of the model as well as serve as the initial center point of K-Means clustering. K-Means algorithm is adopted to cluster and segment each 3D model on the model set. Experimental results show that this algorithm can perform meaningful consistent segmentation on the model set,and the average segmentation accuracy is better.关键词
三维模型/一致性分割/形状直径函数/K均值聚类Key words
3D model/consistency segmentation/SDF/K-Means clustering分类
信息技术与安全科学引用本文复制引用
贾晖,张建刚..基于SDF及K-Means三维模型一致性分割算法∗[J].计算机与数字工程,2019,(9):2141-2144,4.基金项目
国家自然科学基金面上项目"面向图文混合的网络舆情新事件发现及其关联挖掘"(编号:61572399) （编号:61572399）
陕西省教育厅专项科研计划项目"无监督的三维模型集有意义聚类分割技术研究"(编号:15JK1656)资助. （编号:15JK1656）
