【摘要】 提出了一种三维散乱数据的非均匀简化算法,该算法首先将数据集的最小包围盒分割成许多大小相同的立方体,然后,在每个含有数据点的立方体内,计算其所包含曲面的局部法向变化量,并根据用户给定的局部法向变化量门限值将整个三维数据集进行非均匀简化。应用实例验证了算法的有效性。更多还原

【Abstract】 A nonuniform simplification algorithm of unorganized 3D points is presented. At first, the min-max box of the data set is divided into cubes with the same size. Then, for each cube with sampled points in it, the local normal change is calculated and thus the cloud points are nonuniformly simplified according to the user-specified normal change threshold. Finally, the experimental results show that the proposed algorithm is effective.更多还原