[pdal] Point cloud generalisation and feature extraction

[Howard Butler]

Jo,


I would say there probably isn't, as the problem is very loosely defined. Both of your examples leak too, but not so bad that people can't come up with a 'good enough' solution that most people are satisfied with.

What do you mean by simplification? Do you mean decimated points (TIN-style, grid-style, others)? Do you mean simplified by having 'similar' points be segmented together?  Do you mean transformed into 3D surfaces with volumes or edges? Andrew gave pointers to all of the possibilities.

You'll need to be more explicit about what you mean by 'simplified' :)

Howard

PS. Sorry to have missed you in Madison, Wisconsin! Next time you are in the neighborhood, plan to stop by.

> On Sep 12, 2018, at 10:40 AM, Andrew Bell <andrew.bell.ia at gmail.com> wrote:
> 
> Should have also mentioned these filters which are designed for data reduction: https://pdal.io/stages/filters.html#cull <https://pdal.io/stages/filters.html#cull>
> On Wed, Sep 12, 2018 at 11:16 AM Jo Walsh <metazool at fastmail.net <mailto:metazool at fastmail.net>> wrote:
> Good evening PDAL list,
> 
> I've been at a seminar focusing on machine learning applications for palaeontology, thinking of PDAL and not quite sure why. Various folks here have very high resolution laser or LED scans of very small objects and are interested in doing 3D model classification.
> 
> Is there a moral equivalent of GDAL's Polygonize function in PDAL or a Douglas-Peucker like algorithm for point cloud simplification? Is anyone on this list looking at this sort of problem domain? Am I talking out my hat?


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