How to get one non-manifod mesh with adaptive point distribution

Question

all I try to obtain one triangle mesh from one point cloud. The mesh is expected to be manifold, the triangles are well shaped or equilateral and the distribution of the points are adaptive in terms of the curvature. There are valuable information provided on this website.

robust algorithm for surface reconstruction from 3D point cloud?

Mesh generation from points with x, y and z coordinates

I try Poisson reconstruction algorithm, but the triangles are not well shaped.

So I need to improve the quality of the triangles. I learn that centroidal voronoi tessellation(CVT) can achieve that, but I don't know whether the operation will introduce non-manifold vertices and self-intersection. I hope to get some information about it from you.

The mesh from the following post looks pretty good.

How to fill polygon with points regularly?

Delaunay refinement algorithm is used. Can delaunay refinement algorithm apply to triangle mesh directly? Do I first need to delaunay triangulation of the point cloud of the mesh, and then use the information from delaunay triangulation to perform delaunay refinement?

Thanks. Regards Jogging

Answer 1

I created the image in the mentioned post: You can insert all points into a Delaunay triangulation and then create a Zone object (area) consisting of these triangles. Then you call refine(pZone,...) to get a quality mesh. Other options are to create the Zone from constraint edges or as the result of a boolean operation. However, this library is made for 2D and 2.5D. The 3D version will not be released before 2014.

Answer 2

Do you know the BallPivoting approach?