计算机科学 ›› 2011, Vol. 38 ›› Issue (5): 249-251.

• 人工智能 • 上一篇    下一篇

一种随机采样的特征保持的网格简化算法

赵晔,周畅,王昌   

  1. (西北大学数学系 西安710069) (西安工业大学数理系 西安710032) (西安邮电大学数学系 西安710025)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受陕西省自然科学基金(a009JM1019} ,陕西省教育厅专项基金项目(09JK606}资助。

Feature Preserved Mesh Simplification Algorithm Based on Stochastic Sampling

ZHAO Ye,ZHOU Chang,WANG Chang   

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出了一种局部几何特征驱动的随机采样的网格简化算法。该算法首先计算模型中每个三角形的局部几何特征值,根据定义的概率分布函数随机确定每个三角形被选择的概率。然后对选择出的三角形进行三角形折叠,根据折叠前后网格体积变化最小这一准则来确定新生成的顶点的位置。实验证明该算法不仅能使简化前后的模型的体积变化较小,还能有效地保持模型的细节特征。

关键词: 概率分布函数,几何特征,三角形折叠,网格简化

Abstract: This paper presented a new mesh simplification algorithm based on stochastic sampling driving by local geometric feature. First,local geometric feature value of each triangle was computed and the selection probability of the triangle was acquired according to the probability distribution function. Then, the selection triangles were collapsed and new vertices were generated by minimization volume change between the original mesh and the simplify mesh. The expenment results show that mesh models are simplified and the volume is kept while the detail feature is preserved.

Key words: Probability distribution function, Geometric feature, Trianglc collapse, Mmesh simplification

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