<p>There is algorithm called as delaunay triangulation which does triangulation or points it's comparably simple to understand . But it is very slow. If you don't want to implement your own algorithm from scratch please have look at pcl 
<a href="http://pointclouds.org/documentation/tutorials/greedy_projection.php" rel="nofollow noreferrer">http://pointclouds.org/documentation/tutorials/greedy_projection.php</a>
Also have look at CGAL
<a href="http://www.cgal.org" rel="nofollow noreferrer">http://www.cgal.org</a>.</p>

CC BY-SA 3.0
2017-11-28T14:03:21.553Z
As a hint for the people wanting to learn this, the delaunay triangulation can be build with voronoi diagrams. A vornoi diagram takes an unordered set of points and calculates vornoi regions such that each region contains exactly one point and the border of a region is set such that the two points of the bordering fields have exactly the same distance to the border.

Once the voronoi diagram is build, the delaunay triangulation is a simple matter of connecting each point with the points of the neighbouring voronoi regions.
Tare
CC BY-SA 3.0
2017-04-20T05:46:49.803Z
2017-04-20T05:46:49.803Z
PixelClear
<p><em>I'd like to create a mesh from a point cloud generated by video tracking, ideally using python for some kind of prototype at least.</em></p>

<p>Initially I thought this is a fairly easy task, connecting the vertices, creating the faces, done ;) Then I've read that <a href="http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version9.01/" rel="noreferrer">Screened Poisson Surface Reconstruction</a> is currently the best approach. Although there is a nice <a href="https://github.com/mkazhdan/PoissonRecon" rel="noreferrer">github repository</a> and code to play with, it's hard to understand the papers.</p>

<p><strong>Q:</strong> Is there another clever implementation/approach you would recommend or is <em>Screened Poisson Surface Reconstruction</em> the way to go? Any suggestion how to implement that as simple as possible will be greatly appreciated.</p>

CC BY-SA 3.0
2016-12-08T20:02:59.513Z
Could you mention any other requirements? Do you need the fastest / most memory efficient approach, or the simplest one to implement to get on with prototyping?
trichoplax is on Codidact now
CC BY-SA 3.0
2016-12-08T22:52:19.647Z
Maybe this question on stackoverflow helps: [link](http://stackoverflow.com/questions/838761/robust-algorithm-for-surface-reconstruction-from-3d-point-cloud)
wolle
CC BY-SA 3.0
2016-12-09T09:23:47.947Z
Have you tried using [MeshLab](http://meshlab.sourceforge.net/)? It's one of its use cases by design.
IneQuation
CC BY-SA 3.0
2016-12-09T12:12:47.310Z
Performance doesn't matter. I think understanding the concepts and accuracy is more important. Sorry if the question is too broad, but I thought that any experiences from experts, how to dive in and which concept is worth it, would be helpful for me and potential future visitors @trichoplax
p2or
<computational-geometry><mesh>
Creating a mesh from a point cloud?
p2or
# Creating a mesh from a point cloud?

(Asked by: username_0 on 2016-12-08)

*I'd like to create a mesh from a point cloud generated by video tracking, ideally using python for some kind of prototype at least.*

Initially I thought this is a fairly easy task, connecting the vertices, creating the faces, done ;) Then I've read that [Screened Poisson Surface Reconstruction](http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version9.01/) is currently the best approach. Although there is a nice [github repository](https://github.com/mkazhdan/PoissonRecon) and code to play with, it's hard to understand the papers.

**Q:** Is there another clever implementation/approach you would recommend or is *Screened Poisson Surface Reconstruction* the way to go? Any suggestion how to implement that as simple as possible will be greatly appreciated.

**Tags:** computational-geometry, mesh

> **Comments:**
> **username_1**: Could you mention any other requirements? Do you need the fastest / most memory efficient approach, or the simplest one to implement to get on with prototyping?  
> **username_2**: Maybe this question on stackoverflow helps: [link](http://stackoverflow.com/questions/838761/robust-algorithm-for-surface-reconstruction-from-3d-point-cloud)  
> **username_3**: Have you tried using [MeshLab](http://meshlab.sourceforge.net/)? It's one of its use cases by design.  
> **username_0**: Performance doesn't matter. I think understanding the concepts and accuracy is more important. Sorry if the question is too broad, but I thought that any experiences from experts, how to dive in and which concept is worth it, would be helpful for me and potential future visitors @username_1  

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## 1 answers

### Answer by username_4 on 2017-04-20. Score: 2

There is algorithm called as delaunay triangulation which does triangulation or points it's comparably simple to understand . But it is very slow. If you don't want to implement your own algorithm from scratch please have look at pcl
<http://pointclouds.org/documentation/tutorials/greedy_projection.php>
Also have look at CGAL
<http://www.cgal.org>.

> **Comments:**
> **username_5**: As a hint for the people wanting to learn this, the delaunay triangulation can be build with voronoi diagrams. A vornoi diagram takes an unordered set of points and calculates vornoi regions such that each region contains exactly one point and the border of a region is set such that the two points of the bordering fields have exactly the same distance to the border.  Once the voronoi diagram is build, the delaunay triangulation is a simple matter of connecting each point with the points of the neighbouring voronoi regions.  

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