A novel algorithm for NURBS surface reconstruction of unorganized points is presented in this paper.
给出了一个新的散乱数据的NURBS曲面重建算法。
Strategies for surface reconstruction have proceeded in two main directions:reconstruction from unorganized points and reconstruction that exploits the underlying structure of the acquired data.
对于表面的重建策略已经在二个主要的方向着手进行：来自不组织的点和开发已取得数据的在下面结构的重建的重建。
The study of curve reconstruction based on unorganized data points has great importance in reverse engineering.
在反求工程中，基于散乱数据点的曲线重建研究有着重要的意义。
An algorithm for topology reconstruction is promoted that takes as input an unorganized set of points with known density and carries out as output simplicial surfaces.
提出了一种基于曲面局平特性的，以散乱点集及其密度指标作为输入，以三角形分片线性曲面作为输出的拓扑重建算法。
Surface reconstruction of unorganized 3D points is one of the most important research problems on reverse engineering.
三维散乱数据点的曲面重构技术是逆向工程中非常重要的研究课题之一。
A novel algorithm for fitting surface reconstruction of unorganized data points is presented in this paper.
给出了一个新的散乱数据的曲面重建算法。
A systematic scheme is proposed to automatically extract geometric surface features from a point cloud composed of a set of unorganized three-dimensional coordinate points by data segmentation.
给出了数据分块系统性方案，即从仅含有三维坐标的散乱的点云中自动提取几何曲面特性。
A systematic scheme is proposed to automatically extract geometric surface features from a point cloud composed of a set of unorganized three-dimensional coordinate points by data segmentation.
给出了数据分块系统性方案，即从仅含有三维坐标的散乱的点云中自动提取几何曲面特性。
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