In this thesis we summarize the main approaches for surface reconstruction, study the problem of boundary detection for point clouds, and propose a new algorithm based on regular space subdivision.
本文在总结曲面重建主流算法的基础上，对点云的边界检测问题进行了研究，提出了一种基于空间正规分割的边界检测新算法。
Now based on the three-dimensional reconstruction of point cloud, it is to make three-dimensional surface grid model through some algorithm.
目前基于点云的三维重建，大都是通过一些算法构造出三维表面网格模型。
A new region-growing algorithm is presented for triangular mesh surface reconstruction from point-cloud data.
提出一种新的由点云数据生成三角网格曲面的区域增长算法。
This proposed algorithm avoids meshing or reconstructing the point cloud to be local or global surface, and it is suitable for computing geodesic on large scale point cloud.
该算法无需对点云模型进行网格化，无需对点云模型进行局部或全局的曲面重建，适合大规模点云模型上测地线的计算。
This paper proposes a novel algorithm for surface-based hierarchical clustering simplification that aims to accelerate view-dependent point set rendering.
针对点曲面的视点相关绘制问题，提出了一个新的表面基层次聚类简化算法。
The algorithm converts surface matching problem into maximum weight clique searching problem in graph theory, and the optimal point correspondence set is represented by the maximum weight clique.
根据从接收节点得到的反馈信息，提出了一个图模型来刻画基于网络编码的重传问题，并将发送节点的重传策略模型化为图中的最小团划分。
The algorithm converts surface matching problem into maximum weight clique searching problem in graph theory, and the optimal point correspondence set is represented by the maximum weight clique.
根据从接收节点得到的反馈信息，提出了一个图模型来刻画基于网络编码的重传问题，并将发送节点的重传策略模型化为图中的最小团划分。
应用推荐