Kevin Wampler wrote:
> Kevin Wampler wrote:
>> Tom Austin wrote:
>>> Anyone have any brain matter than they can throw out about how to 
>>> work with large point clouds?
>>
>> That depends quite a bit on what you want to do with them or use them 
>> for.
> 
> Man, I was curious!  I really am more than happy to help, it's just that 
> which algorithm you want to use depends on the application.  As a 
> general suggestion, spatial partitioning hierarchies (like octrees or 
> kd-trees) are good when you want to quickly do operations that are 
> localized around a small area in space, but that's about the most I can 
> say without knowing more.

Sorry about the delayed response - been VERY busy lately and have not 
had much other time.  I guess given the economic climate this is a good 
thing.


Essentially I am using a 3D laser based scanner to gather portions of 
mine tunnels.  The scanner gathers data as points in a spherical format.

   I estimate that there will be ~150 separate scans totaling ~30 
million points.


I currently deal with the scans only as point clouds.

I have methods to align the scans.

I can put all of the points into one large point cloud that has 30 
million points.



What I am looking for is:


Methods or programs to 'simplify' the resulting point cloud so that it 
still is a fair representation of the overall area, but has much fewer 
points ~300k.

Methods or programs to create a single mesh of the resulting point cloud 
that can represent tunnels.



I've 2D draped for a mesh before - that's no problem.  It's the 3D 
meshing of arbitrary points that I have not experienced yet.

I'm pretty good about taking an approach (steps or algorithm) and 
putting them into code.



If you would like more info just ask questions and I will provide what I 
can.

I might be able to dig up some past work that is similar to what I am 
trying to do.



Tom

Post a reply to this message