Hi, I just read the article linked in the M3C2 menu. (the article from D. Lague, N. Brodu and J. Leroux (Geosciences Rennes))
Just want to say that's a brilliant idea to have this method especially for natural surface comparison.
My question will be: can I run the similar experiment described by the article using CloudCompare to determine the optimum D and d and compute the standard deviation, normal error for both? (I mean for example with a range of D from 0.5m to 20m, I want to see how the E-normal change with my selection).
Thanks!
Questions about M3C2 distance measurement
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xiaoxiaozhu007
- Posts: 3
- Joined: Fri Sep 30, 2016 10:21 pm
Re: Questions about M3C2 distance measurement
Not sure to fully understand your question... but I guess you can perfectly do what you want with the plugin.
We should wait for Dimitri's answer however.
We should wait for Dimitri's answer however.
Daniel, CloudCompare admin
Re: Questions about M3C2 distance measurement
Hi,
glad you liked the approach in M3C2 ;-)
Unfortunately, there's no simple way to get the data for all scales in one single operation. If you choose optimal scale, you'll get the standard deviation for the optimal scale only which may vary from point to point.
A solution, is...to run M3C2 successively for various scales (using a constant scale) with the same core point file, and then bring everything together (outside cloudcompare)...not ideal, I know.
Alternatively, you may use the very old command line version still available (I think) on Nicolas Brodu website or mine (not sure). It has much more options that in CC (but it is far less optimized) There's an option (if I remember well) to output the standard deviation for every scale. Or at least, it's very easy to write a batch in which you systematically vary the normal scale or the projection scale systematically to explore how the standard deviation varies.
Dimitri
glad you liked the approach in M3C2 ;-)
Unfortunately, there's no simple way to get the data for all scales in one single operation. If you choose optimal scale, you'll get the standard deviation for the optimal scale only which may vary from point to point.
A solution, is...to run M3C2 successively for various scales (using a constant scale) with the same core point file, and then bring everything together (outside cloudcompare)...not ideal, I know.
Alternatively, you may use the very old command line version still available (I think) on Nicolas Brodu website or mine (not sure). It has much more options that in CC (but it is far less optimized) There's an option (if I remember well) to output the standard deviation for every scale. Or at least, it's very easy to write a batch in which you systematically vary the normal scale or the projection scale systematically to explore how the standard deviation varies.
Dimitri