数据精简是进行曲面重构的重要内容。通过分析现有精简方法的不足,采用了根据曲率变化对原始散乱点云进行精简的方法,重点研究了散乱点云的空间划分、邻域搜索、曲率估算和曲率精简原则。对具有不同特征的测量数据进行了精简分析,实验结果表明该方法得到了更合理的精简效果。
Data simplification is an important part of surface reconstruction. Through analyzing the shortcomings of existing data simplification methods, a simplification method based on curvature variance of original scattered point cloud is adopted. This method emphasizes on the algorithms for spatial partition, neighborhood searching, curvature estimation and the principles of simplification. Through testing and analyzing some measured data with different characteristics, the results show that the algorithms achieve more reasonable effect of simplification.