CGAL users discussion list

[Simon Giraudot <>]

Hello again,
> In my case, the massive point cloud is a laser scan of an indoor
> environment.
> At a later procedure, I will have to call Advanced Front Face Reconstruction
> (I guess in my case, it is a better choice than Poisson, because I want to
> fit planes and cylinders)
> But the next step I am going to do is shape detection and structuring.
> I am still thinking if I should do simplification and edge aware upsampling.
You only need unoriented normals for all of these algorithms (except 
Poisson but as you said, it might not be the best choice), so if I were 
you, I would save some time and I wouldn't orient them.
> > > And yes, if I set k=6, it seems MST can only manage to orientate one
> > > point, so the code block erase all other points except one single point.
> > > But setting a bigger K, say 12, already eat up all of my main memory and
> > > swap space.
This is very weird, but then again, I can imagine something going wrong 
depending on the uniformity/density of your point cloud.

One thing you could do first would be to extract a small portion of your 
point cloud and see if the parameters work well on it (k=6, k=12, etc.). 
This way, at least, you can do some tests without the memory issue. 
Separating the point cloud in smaller subparts and applying orientation 
to each is an option, but of course, in that case, there is not 
guarantee that orientation will be consistent from one point cloud to 
another.

Best regards,

--
Simon Giraudot, PhD
R&D Engineer
GeometryFactory - http://geometryfactory.com/