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Analyzing surface sampling patterns using the localized pair correlation function
  • ISSN号:1008-9497
  • 期刊名称:《浙江大学学报:理学版》
  • 时间:0
  • 分类:TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:NLPR-LIAMA, Institute of Automation, Chinese Academy of Sciences
  • 相关基金:partially funded by the National Natural Science Foundation of China (Nos. 61372168, 61571439, 61572502, and 61271431);the National High-tech R&D Program of China (863 Program) (No. 2015AA016402)
中文摘要:

Point distributions with different characteristics have a crucial influence on graphics applications. Various analysis tools have been developed in recent years, mainly for blue noise sampling in Euclidean domains. In this paper, we present a new method to analyze the properties of general sampling patterns that are distributed on mesh surfaces. The core idea is to generalize to surfaces the pair correlation function(PCF) which has successfully been employed in sampling pattern analysis and synthesis in 2D and 3D. Experimental results demonstrate that the proposed approach can reveal correlations of point sets generated by a wide range of sampling algorithms. An acceleration technique is also suggested to improve the performance of the PCF.

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期刊信息
  • 《浙江大学学报:理学版》
  • 中国科技核心期刊
  • 主管单位:教育部
  • 主办单位:浙江大学
  • 主编:贺贤士 张富春
  • 地址:杭州市天目山路148号
  • 邮编:310028
  • 邮箱:zdxb_l@zju.edu.cn
  • 电话:0571-88272803
  • 国际标准刊号:ISSN:1008-9497
  • 国内统一刊号:ISSN:33-1246/N
  • 邮发代号:32-36
  • 获奖情况:
  • 第二届中国高校精品科技期刊
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国化学文摘(网络版),美国数学评论(网络版),英国农业与生物科学研究中心文摘,波兰哥白尼索引,德国数学文摘,荷兰文摘与引文数据库,美国剑桥科学文摘,英国动物学记录,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2014版)
  • 被引量:7855