Re-Sampled Based Mixed Surface Reconstruction Algorithm

A novel mixed surface reconstruction algorithm based on re-sample is proposed to improve the reconstructed feature quality and solve the problem of surface intersection. First, the local feature scale is employed to judge the sample density of initial sample point set, and consequently the redundant sample points are deleted. Meanwhile, the necessary sample points are plugged into the deficient feature areas. And then, the Delaunay triangulation algorithm is used to reconstruct the geometrical structure of re-sampled point set. At last, effective triangles are drawn out based on screw incrementing method to reconstruct the grid surface of the scattered point set. Experimental results show that the proposed algorithm is robust and effectively.