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点的邻域的英文

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"点的邻域"怎么读用"点的邻域"造句

英文翻译手机手机版

  • neighborhood of a point

例句与用法

  • We using the triangulation constructed from the point ' s adjacent field , which is the nearest to the original local surface , to compute the point ' s normal . it can get a good result
    本文采用了与局部曲面片最接近的由点的邻域所构造的三角片来近似求点的法向量的方法,得到了较好的实验结果。
  • The dividing process is recorded by octree , and then we make out the rapid adjacent - field searching algorithm using envelopment - box ' s recursion feature . this algorithm can also kick off some noise - points from the data cloud . it make the consequent process of surface reconstruction more convenience and precise
    分割过程采用八叉树来记录,并利用包围盒的递归特性实现了点的邻域的快速搜索算法,同时可以有效地排除噪声点,显著减少了密集散乱数据点云几何建模所花费的时间,提高了建模效率。
  • It made use of randomly sampled one edge - point sampling randomly and locally searched two edge - points in an image and information of their neighborhoods to determine a candidate ellipse , then affirmed true ellipse for the candidate ellipse by affirming true circle for corresponding circle into which is transformed by the candidate ellipse
    该算法利用在图像中随机采样到的一个边缘点和局部搜索到的两个边缘点以及这三个点的邻域信息确定候选椭圆,再将候选椭圆变换为对应圆,通过确认真圆来确认真椭圆。
  • Based on data cloud , which is measured from 3 - coordinate measuring machine ( cmm ) or so , an algorithm to search lopological structure from 3d unorganized points using envelopment - box technology is proposed in this thesis . based on this method , we searching neighbor points of sampling point . we also improve the max - min angle criteria to realize local triangulation , and then get the normal of sampling point from the triangulation
    本文以测量得到的曲面数据点点云为基础,提出了一种基于包围盒的自动寻找三维散乱数据点之间拓扑结构的方法,采用该方法寻找采样点的邻域结点,并对三角剖分中的典型优化准则?最小内角最大准则提出了改进,按照改进后的优化准则实现了采样点的局部三角划分,并进一步求解得到采样点的法向量,依据法向量及邻域拓扑关系在二次曲面的基础上实现了散乱数据曲面重构中的数据点的自动分类。
用"点的邻域"造句  
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