On 10/28/2016 3:21 PM, scott wrote:
>> If I understand what you said. Voxel data can be or is a subset of point
>> cloud data.
>
> Yes, voxel data could just be thought of as point cloud data where all
> the points are on a finite uniform grid (with no empty cells) within
> known limits. In which case it becomes more efficient to store the data
> as a list of values (colour, transparency, whatever) in some agreed
> order, rather than listing the coordinates of every point.
>
> Point cloud data is totally arbitrary, you could have points 1mm apart
> in one area, but points meters apart in others. This is usual if you got
> the data from a laser scanner. The coordinates of each point could be
> anything (within the resolution of the number format you are using), so
> are not on a grid or equally spaced at all.
>
> Think in 2D, voxel data is like a bitmap image, whereas point cloud data
> is like a list of 2D coordinates


Yes, but how is the list ordered if at all, at all?

(perhaps with associated information
> like colour as clipka mentioned).
>
>> So what is the problem with redefining coordinates in a df3 to points or
>> small spheres instead of a cubical volume?
>
> My guess is all the algorithms used to render df3's won't work with just
> an arbitrary list of point coordinates.
>


I never thought they would. But...
You could turn point cloud data into a df3 by defining a resolution and 
using that to dived the cloud (magically by hard sums) into averaged voxels.

Not that I am asking anyone to implement this.
'Just exploring.

-- 

Regards
     Stephen

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