I'm working on a 3D Shock Fitting solver for numerical computations of hypersonic reentry flows and I included CGAL in my project. I need to reconstruct a 3D triangular surface from a set of cloud points. I'm using the CGAL Point Set Processing package for processing the cloud point set ( using WLOP-Normal Estimation-Smoothing) and the Advancing Front Surface Reconstruction package for the surface mesh generation.
Being the first time I use CGAL, I'm quite happy for the results, but I need to improve the quality of the reconstructed surface, in terms of number of points and regularity of the edge. I tried to apply almost every possible function and parameters value in the Point Set Processing package, without any improvement on the overall quality. An important aspect of this reconstruction is the location of the surface compared to point cloud. I need to fit an "expected" position and shape of the surface, but upsampling or smoothing differently the points gives me a bad fit.
Can you suggest me a different strategy for this surface reconstruction problem? Is it possible to remesh my surface with a different package after the reconstruction?
I attached the point cloud set ( just to give you an idea of the points distribution ), the best result I got with CGAL and the "desired" surface I would like to achieve ( in terms of smoothing and points sampling)