点云数据的曲面重构新算法

针对采用视觉测量方式得到的点云数据特点，提出了基于动力学数值仿真的网格曲面逼近方法。依据曲面曲率变化特性，该方法可对点云数据进行自适应压缩，并能显著提高逼近网格的品质，从而实现了点云数据的精确曲面重构。实际的算例结果表明，该方法实用可靠。

For the large-scale data cloud, an algorithm of triangular patch approximation, based on the dynamic simulation, is presented in this paper. According to the change characteristics of surface curvature, the large-scale data cloud can be reduced to the reasonable scale and well-shaped triangles can also be created by this approach. Thus the precise reconstruction of data cloud is realized. The experimental results testify that the approach is feasible.

中科院沈阳自动化研究所开放基金资助项目