CGAL triangulation of 3D polygon with no new points - cgal

Apologies if this is a simple question, I am quite new to CGAL and computational geometry in general.
I have a polygon defined in 3D space (i.e. a set of points in R^3 and edges connecting exactly two points). In fact, the polygon is exactly the hole of a surface mesh. My question is how to triangulate that polygon without introducing any new points in the interior of the polygon. The resulting triangulation must contain only the original points on the boundary of the polygon. Is this possible in CGAL?

Related

Algorithm/optimization for area minimizing hull

Assuming I have several points in a 2D plane.
I now want to create a hull that covers all points. The shape of that hull should be somehow weighted by the distance/closeness of the points, i.e., outsiders must be connected to the rest of the points by a narrow link (see target state).
Figure 2 also shows a hull that is covering all points, however, does not narrow down the link to the three outliers.
I also do not want an alpha-shape or convex hull because that would not obfuscate the location of my points, because I can retrieve the location from the vertices.
Is there any area of algorithms/optimizations that covers this kind of problem?

3d surface triangulation of an open surface with CGAL

I'm a newbie to CGAL library. However, I think it's a very suitable package for what I want to do.
I have a set of points representing a 3D surface (as shown in figure 1).
I want to fit a 3d triangulation on this surface. The surface is not closed and therefore does not occupy a volume. The code provided in poisson_reconstruction_example.cpp seems appropriate for this job. But the problem is that as a part of poisson_reconstruction algorithm it closes the ends and underneath of the surface to make it a volume (see figure2).
I was wondering:
1- Is there a way to do the triangulation on the surface just defined by the points, without getting a closed surface which encloses a finite volume?
This means that the final triangulation has boundary edges.
I'm happy with any Upsampling or smoothing which may be needed.
2- If the answer to the first question is no, then, is there any way to guarantee that the input points are the vertices of the generated triangles?
The poisson surface reconstruction generates a close surface that interpolates the point cloud given as input. It requires as input a point set with normals.
If you need a algorithm that only uses input points in the output, you can try the Advancing Front Surface Reconstruction algorithm.

CGAL 2D delaunay triangulation with mixed boundary conditions

I am new to CGAL, so I do not know where to start.
I want CGAL to calculate a delaunay triangulation of a set of points in 2D. My problem is that there is a class for nonperiodic systems and another one for periodic systems (sorry, can not post more than 2 links), but none for mixed periodic and nonperiodic systems.
Imagine something like this, which is periodic in x direction.
For your information: The vertices near the upper und lower boundary are connected to vertices far from y=0, but this not particularly relevant to the problem.
Is there any easy way to achieve this or do I need to implement this manually?
The 2D Periodic triangulation package in CGAL only handle periodicity in the x and y direction (i.e triangulation in the two dimensional flat torus).

Tetrahedralization from surface mesh of thin-walled object

I need to generate a tetrahedral (volume) mesh of thin-walled object object. Think of objects like a bottle or a plastic bowl, etc, which are mostly hollow. The volumetric mesh is needed for an FEM simulation. A surface mesh of the outside surface of the object is available from measurement, using e.g. octomap or KinectFusion. Therefore the vertex spacing is relatively regular. The inner surface of the object can be calculated from the outside surface by moving all points inside, since the wall thickness is known.
So far, I have considered the following approaches:
Create a 3D Delaunay triangulation (which would destroy the existing surface meshes) and then remove all tetrahedra which are not between the two original surfaces. For this check, it might be required to create an implicit surface representation of the 2 surfaces.
Create a 3D Delaunay triangulation and remove tetrahedra which are "inside" (in the hollow space) or "outside" (of the outer surface) with Alphashapes.
Close the outside and inside meshes and load them into tetgen as the outside hull and as a hole respectively.
These approaches seem to be a bit inelegant to me, and they still have some pitfalls. I would probably need several libraries/tools for them. For 1 and 2, probably tetgen or another FEM meshing tool would still be required to create well-conditioned tetrahedra. Does anyone have a more straight-forward solution? I guess this should also be a common problem in 3D printing.
Concerning tools/libraries, I have looked into PCL, meshlab and tetgen so far. They all seem to do only part of the job. Ideally, I would like to use only open source libraries and avoid tools which require manual intervention.
One way is to:
create triangular mesh of surface points,
extrude (move) that surface to inner for a given thickness. That produces volume (triangular prism) mesh of a wall,
each prism can be split in three tetrahedrons.
The problem I see is aspect ratio.
A single layer of tetrahedra will not reproduce shell or bending behavior very well. A single element through the thickness will already require a large mesh. Putting more than one will likely break the bank in order to keep aspect ratios and angles acceptable.
I'd prefer brick or thick shell elements to tetrahedra in this case. I think the modeling will be easier and the behavior will be more faithful to the physics.

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

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
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.
Do you know the BallPivoting approach?