CGAL- How to generate a adaptive sampling on surface?

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CGAL- How to generate a adaptive sampling on surface?

Frank Dz
Hi everyone~ I want to know how to get adaptive sampling on surface. The
'adaptive' means the samples on feature part can be more dense.

I have tried search about this. Yet I only get some surface reconstruction
method or mesh generation method have this effect. However, it is not
*sampling on the Original Surface*.

I just wonder if there exist some sampling method in CGAL. Or I didn't find
it without using a right name describing it.

Thanks for you kind help and guidance.



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Re: CGAL- How to generate a adaptive sampling on surface?

Sebastien Loriot (GeometryFactory)
There is the function sample_triangle_mesh() but the sampling is more or
less "uniform". You can look at the implementation of the function and
modify it to match what you are trying to achieve.
If you hack the part where the area of the triangles is used as the
probabilistic weight to be selected you might be able to achieve
something close to what you want.

Sebastien.

https://doc.cgal.org/latest/Polygon_mesh_processing/group__PMP__distance__grp.html#ga7874c0f16badf7b7939039cf979ad16d

On 12/16/19 2:02 PM, Frank Dz wrote:

> Hi everyone~ I want to know how to get adaptive sampling on surface. The
> 'adaptive' means the samples on feature part can be more dense.
>
> I have tried search about this. Yet I only get some surface reconstruction
> method or mesh generation method have this effect. However, it is not
> *sampling on the Original Surface*.
>
> I just wonder if there exist some sampling method in CGAL. Or I didn't find
> it without using a right name describing it.
>
> Thanks for you kind help and guidance.
>
>
>
> --
> Sent from: http://cgal-discuss.949826.n4.nabble.com/
>

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Re: CGAL- How to generate a adaptive sampling on surface?

Frank Dz
Thx for you kind help! Before I tried to find a adaptive sampling method, I
adopted blue noise sampling in my project, which is also under a uniform
meaning.

Any way, I will try to make it!

Thank you again!


Best regards,

Frank



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