首页> 中文期刊> 《计算可视媒体(英文版)》 >Surface remeshing with robust user-guided segmentation

Surface remeshing with robust user-guided segmentation

         

摘要

Surface remeshing is widely required in modeling, animation, simulation, and many other computer graphics applications. Improving the elements’ quality is a challenging task in surface remeshing. Existing methods often fail to efficiently remove poor-quality elements especially in regions with sharp features. In this paper, we propose and use a robust segmentation method followed by remeshing the segmented mesh. Mesh segmentation is initiated using an existing Live-wire interaction approach and is further refined using local mesh operations. The refined segmented mesh is finally sent to the remeshing pipeline, in which each mesh segment is remeshed independently. An experimental study compares our mesh segmentation method as well as remeshing results with representative existing methods. We demonstrate that the proposed segmentation method is robust and suitable for remeshing.

著录项

  • 来源
    《计算可视媒体(英文版)》 |2018年第2期|P.113-122|共10页
  • 作者单位

    National Laboratory of Pattern Recognition, Instituteof Automation, Chinese Academy of Sciences;

    University of Chinese Academy of Sciences;

    National Digital Switching System Engineering& Technological Research Center;

    National Laboratory of Pattern Recognition, Instituteof Automation, Chinese Academy of Sciences;

    University of Chinese Academy of Sciences;

    National Digital Switching System Engineering& Technological Research Center;

    National Laboratory of Pattern Recognition, Instituteof Automation, Chinese Academy of Sciences;

    University of Chinese Academy of Sciences;

    National Digital Switching System Engineering& Technological Research Center;

    National Laboratory of Pattern Recognition, Instituteof Automation, Chinese Academy of Sciences;

    University of Chinese Academy of Sciences;

    National Digital Switching System Engineering& Technological Research Center;

    National Laboratory of Pattern Recognition, Instituteof Automation, Chinese Academy of Sciences;

    University of Chinese Academy of Sciences;

    National Digital Switching System Engineering& Technological Research Center;

  • 原文格式 PDF
  • 正文语种 CHI
  • 中图分类 TP391.41;
  • 关键词

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号