CGAL users discussion list

[Simon Giraudot <>]

Hello,

> [Update]
> I have tried k=6, where it also used 43660 Mb main memory.
If I understand correctly, the code stores a graph that would k*N in 
size (with N your number of points). I've tried on a 6 million points 
and k=19 and the RAM usage goes to 7GB, so I'm not really surprised by 
your results on such a large point cloud. I'll have a look into the code 
to see if something can be improved…

For the record, what do you need oriented normals for? Many algorithms 
only require unoriented normals (I can mostly think of Poisson 
reconstruction in CGAL which does require orientation).
> But the resulting point cloud only being erased to one single point by the
> code block:
>
>    // Optional: delete points with an unoriented normal
>    // if you plan to call a reconstruction algorithm that expects oriented
> normals.
>    points.erase(unoriented_points_begin, points.end());
I'm not sure I understand what's your problem here: does this erase ALL 
of your points except for one? Or something else?

I don't know if this is your case, but just a note: algorithms that are 
applied to K nearest neighbors can give incorrect and unexpected results 
if the point cloud is highly non-uniform (for example, if you have very 
dense scanlines with a high space between each scanline).

Best,

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