[SciPy-User] Tessellating PointCloud (ConvexHull? Delaunay)

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[SciPy-User] Tessellating PointCloud (ConvexHull? Delaunay)

Samuel Maybury
Hi guys,
Been looking to tesselate a 3D point cloud from array of form [[x1 y1 z1][x2 y2 z2]...[xn yn zn]].
I tried scipy.spatial.convexhull which worked decently, but has the notable limitation of not handling concaves. The STL I then extracted only had half the triangles, but I think I need to take that up with the maker of numpy-stl.
Still kinda new to scipy (and programming in general) so could someone informed please help?
From what I understand Delaunay triangulates every point in the cloud. Is there a way to limit it to only Tessellating to the nearest?
Or a better method for doing this?

Many thanks,
                      Sam

CV:             engineering.community/profile/samuel-maybury/about


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Re: Tessellating PointCloud (ConvexHull? Delaunay)

Robert Kern-2
On Wed, Mar 7, 2018 at 2:15 PM, Samuel Maybury <[hidden email]> wrote:
>
> Hi guys,
> Been looking to tesselate a 3D point cloud from array of form [[x1 y1 z1][x2 y2 z2]...[xn yn zn]].
> I tried scipy.spatial.convexhull which worked decently, but has the notable limitation of not handling concaves. The STL I then extracted only had half the triangles, but I think I need to take that up with the maker of numpy-stl.
> Still kinda new to scipy (and programming in general) so could someone informed please help?
> From what I understand Delaunay triangulates every point in the cloud. Is there a way to limit it to only Tessellating to the nearest?
> Or a better method for doing this?

As I said before, Delaunay triangulation doesn't do much for reconstructing a surface from a point cloud. Following the MeshLab references[1], it looks like variants of a technique called Poisson reconstruction are standard these days. Googling finds these Python projects, but I have no experience with them:


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Re: Tessellating PointCloud (ConvexHull? Delaunay)

Samuel Maybury
Thanks Robert,
I can honestly say I hadn’t seen that before! I’ve looked at so many libraries but that may just be the ultimate answer! 
I did extract a near-usable STL with convex hull so glad to say it almost works.
I’ll give that a go and you have have this honour student’s thanks :)

Best wishes,
    Sam

On 7 Mar 2018, at 22:32, Robert Kern <[hidden email]> wrote:

On Wed, Mar 7, 2018 at 2:15 PM, Samuel Maybury <[hidden email]> wrote:
>
> Hi guys,
> Been looking to tesselate a 3D point cloud from array of form [[x1 y1 z1][x2 y2 z2]...[xn yn zn]].
> I tried scipy.spatial.convexhull which worked decently, but has the notable limitation of not handling concaves. The STL I then extracted only had half the triangles, but I think I need to take that up with the maker of numpy-stl.
> Still kinda new to scipy (and programming in general) so could someone informed please help?
> From what I understand Delaunay triangulates every point in the cloud. Is there a way to limit it to only Tessellating to the nearest?
> Or a better method for doing this?

As I said before, Delaunay triangulation doesn't do much for reconstructing a surface from a point cloud. Following the MeshLab references[1], it looks like variants of a technique called Poisson reconstruction are standard these days. Googling finds these Python projects, but I have no experience with them:

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