I want to generate surface mesh(3d triangle mesh) non-uniformly,How can I do it with CGAL?
when I use Polygon Mesh Processing package,I got result like this:
all the triangle have almostly same size
But I want to generate triangle mesh like this:
different area have different triangle size, I mean it is adaptively.
It also called anisotropic mesh
Thanks very much!
The function you used in the Polygon Mesh Processing package is named isotropic_remeshing(). Isotropic basically means that all triangles will have the same size. If you want to have more control on the size of the triangles you need to use another method like those in the Mesh_3 package.
You can have a look at this example.
Related
So what I want to do is render each material 1 at a time. Which means that each Material will have it's own vertices. Is there some kind of function within Assimp when I process a mesh that will tell me which material the vertices belong to.
Of course I would put the position, the normal and the texCoord in the vertex and I need the induces.
There is no query to get these meshes implemented in Asset-Importer-Lib right now. But you can write this easily by yourself:
Import your model
Check whether there are any meshes loaded
Loop over all meshes stored in aiScene
Sort them for meshes with the same material index
Loop over all vertices of the list of meshes.
I wrote a blog-post about that: Batch-Rendering for Assimp-Scene
thanks for reading this question. My title is basically what I'm trying to achieve. I did a poisson surface mesh generation using Poisson_surface_reconstruction_3(cgal). I can't figure out how to map the node identities of my resulting surface mesh into my starting point sets?
The output of my poisson surface generation is produced by the following lines:
CGAL::facets_in_complex_2_to_triangle_mesh(c2t3, output_mesh);
out << output_mesh;
In my output file, there are some x y z coordinates, followed by a set of 3 integers each line, I think they indicates which nodes form a delaunay triangle. The problem is that the output points do not correspond to my initial point set, since not any x y z value match to any of my original points. Yet I'm trying to figure out which points are forming a delaunay triangles in my original point set.
Could someone suggest me how can I do this in cgal?
Many thanks.
The poisson recontruction algorithm consist in meshing an implicit function that somehow fits you input points. In practice, it means that you input point will no belong to the set of points of the output surface, and won't even lie exactly on triangles of the output surface. However, they should not be too far from the output surface (except if you have some really sparse sampling parts).
What you can do to locate your input points with the output surface is to use the function closest_point_and_primitive() from the AABB-tree class.
Here is an example of how to build the tree from a mesh.
I have a series of straight line segments of varying thickness connected end-to-end to create meandering path. Does anyone know a way to paint this as a smooth meandering line, sort of like vectorizing it? I am using QPainter. I haven't had any success finding an appropriate function in QPainterPath.
The data looks something like this:
[(QPointF, width), (QPointF, width), (QPointF, width), ... ]
Thanks!
EDIT: Added example image
I wanted to leave it open to creative responses, but I am just looking to move from linear interpolation (QPainter::drawLine()) to spline interpolation.
If I understand your question correctly...
Don't draw a line, draw a filled polygon that encloses your line data with the right thickness. Drawback: That requires calculations on your data beforehand.
In my meshing application I will have to specify fix points within a domain. The idea is that, the fix points must also be the element points after the domain is being meshed.
Furthermore, the elements around the fix points should be more dense. The general concept is that for the fix points, there should exist a radius r around those points, such that the mesh size inside r is of different sizes than outside of the r. The mesh sizes inside and outside of the r should be specifiable.
Are these two things doable in CGAL 2D Mesh algorithm?
Using your wording, all the input point of the initial constrained Delaunay triangulation will be fix points, because the 2D mesh generator only insert new points in the triangulation: it never removes any point.
As for the density, you can copy, paste, and modify a criteria class, such as CGAL::Delaunay_mesh_size_criteria_2<CDT> so that the local size upper bound is smaller around the fix points.
Now, the difficulty is how to implement that new size policy. Your criteria class could store a const reference to another Delaunay_triangulation_2, that contains only the fixed points you want. Then, for each triangle query, you can call nearest_vertex and then actually check if the distance between the query point is smaller that the radius bound of your circles. For a triangle, you can either verify that for only its barycenter, or for all three points of the triangle. Then, according to the result of that/those query(s), you can modify the size bound, in the code of your copy of CGAL::Delaunay_mesh_size_criteria_2<CDT>.
Yes, no points will be removed from the triangulation by the mesher.
Note however that if you insert points too close to a constraint this will induce a refinement of the constraint while it is not Gabriel.
I have a 3D model, which consists of the 3D triangular meshes. I want to partition the meshes into different groups. Each group represents a surface, such as a planar face, cylindrical surface. This is something like surface recognition/reconstruction.
The input is a set of 3D triangular meshes. The output is the mesh segmentations per surface.
Is there any library meets my requirement?
If you want to go into lots of mesh processing, then the point cloud library is a good idea, but I'd also suggest CGAL: http://www.cgal.org for more algorithms and loads of structures aimed at meshes.
Lastly, the problem you describe is most easily solved on your own:
enumerate all vertices
enumerate all polygons
create an array of ints with the size of the number of vertices in your "big" mesh, initialize with 0.
create an array of ints with the size of the number of polygons in your "big" mesh, initialize with 0.
initialize a counter to 0
for each polygon in your mesh, look at its vertices and the value that each has in the array.
if the values for each vertex are zero, increase counter and assign to each of the values in the vertex array and polygon array correspondingly.
if not, relabel all vertices and polygons with a higher number to the smallest, non-zero number.
The relabeling can be done quickly with a look up table.
This might save you lots of issues interfacing your code to some library you're not really interested in.
You should have a look at the PCL library, it has all these features and much more: http://pointclouds.org/