Hello all,
I am comparing two clouds of the same model using C2C distance analysis.
Is there an option or possibility to compute the non-absolute Z-distances? I wand to investigate if one scan is tilted in respect to the other - to do so, I need to know if the Z-distances are positive or negative.
The M3C2 plugin seem to have this possibilty - but I'm not very comfortable with their normals and projection parameters.
Thanks a lot for your help,
Florian
C2C non-absolute distances
Re: C2C non-absolute distances
He he, if you want signed distances then you need normals ;)
You have multiple choices:
[*] either compute a triangular mesh on your reference point cloud (with Delaunay or Poisson)
[*] or using M3C2 indeed (if you don't want to 'fight' with M3C2 options, you can compute the normals yourself on the reference cloud prior to calling the plugin - with Edit > Normals > Compute)
You have multiple choices:
[*] either compute a triangular mesh on your reference point cloud (with Delaunay or Poisson)
[*] or using M3C2 indeed (if you don't want to 'fight' with M3C2 options, you can compute the normals yourself on the reference cloud prior to calling the plugin - with Edit > Normals > Compute)
Daniel, CloudCompare admin
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Re: C2C non-absolute distances
Hello Daniel,
I re-opened the post because I have a similar question.
I do not understand why we need normals to have signed X, Y or Z-distances ? I understand for the global distance between the two points but why for the distance on each dimension ?
Maybe I don't understand something but when we choose to split X,Y,Z on the C2C algorithm we should have sign for each dimension, is'n it ? But it is not the case these values are always positive...
Let's take an example, if we have a point A(3,6,6) in a first point cloud (reference) and B(3,6,2) the closest point of A in a second point cloud (to compare). Then the absolute distance is D=sqrt(0+0+16)=4; and the coordinates of the vector AB are (0,0,-4) so on the Z axis there is a distance of -4 (i.e 4 units down).
Is there a way to have this information : the real (and not absolute) coordinates of the vectors between the closest points of two point cloud ?
I am working on tree growth. Using this information (i.e vector coordinates) for two point cloud of a tree at several years interval I can figure if the tree grows (or at least displace) more horizontally than vertically or the contrary...
Thanks a lot
best regards
Olivier
I re-opened the post because I have a similar question.
I do not understand why we need normals to have signed X, Y or Z-distances ? I understand for the global distance between the two points but why for the distance on each dimension ?
Maybe I don't understand something but when we choose to split X,Y,Z on the C2C algorithm we should have sign for each dimension, is'n it ? But it is not the case these values are always positive...
Let's take an example, if we have a point A(3,6,6) in a first point cloud (reference) and B(3,6,2) the closest point of A in a second point cloud (to compare). Then the absolute distance is D=sqrt(0+0+16)=4; and the coordinates of the vector AB are (0,0,-4) so on the Z axis there is a distance of -4 (i.e 4 units down).
Is there a way to have this information : the real (and not absolute) coordinates of the vectors between the closest points of two point cloud ?
I am working on tree growth. Using this information (i.e vector coordinates) for two point cloud of a tree at several years interval I can figure if the tree grows (or at least displace) more horizontally than vertically or the contrary...
Thanks a lot
best regards
Olivier
Re: C2C non-absolute distances
The X, Y and Z distance are signed when computed with the 'split X, Y and Z components' option.
I just checked with the latest version (2.6.3.beta) and it works fine. Are you sure you display the right scalar field?
Otherwise, don't hesitate to send me your clouds (or a small subset).
I just checked with the latest version (2.6.3.beta) and it works fine. Are you sure you display the right scalar field?
Otherwise, don't hesitate to send me your clouds (or a small subset).
Daniel, CloudCompare admin
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- Posts: 16
- Joined: Wed Apr 29, 2015 10:24 pm
- Location: Québec, Canada
Re: C2C non-absolute distances
Hello Daniel,
I just installed the latest version and it works well.
Thank you very much.
Olivier
PS: note that it doesn't work for the version 2.6.1 (i.e X, Y and Z are always positive).
I just installed the latest version and it works well.
Thank you very much.
Olivier
PS: note that it doesn't work for the version 2.6.1 (i.e X, Y and Z are always positive).
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- Joined: Mon Oct 15, 2018 2:08 am
Re: C2C non-absolute distances
Hello everyone. I am a new user of cloud compare and I am trying to compare cloud to cloud distances. I have two point clouds overlapped on each other with a certain common area. The values are as shown in the figure and I would like to know the value of c2c distances instead of a bar. Can you please let me know how I can do that ? Thanks!
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- compare.JPG (135.75 KiB) Viewed 4119 times
Re: C2C non-absolute distances
If you want to see particular distance values associated to particular points, you can use the 'shift + left click' shortcut to spawn a label on a point (or use the 'Point picking' tool: http://www.cloudcompare.org/doc/wiki/in ... nt_Picking).
You can change the colors/parameters of the currently displayed scalar field (see http://www.cloudcompare.org/doc/wiki/in ... properties and http://www.cloudcompare.org/doc/wiki/in ... es_Manager) to get a better visualization of what's happening in the part of interest. You can also extract the points below a given distance (or equivalently set a maximum distance when you compute the distances).
Otherwise you can also export all the values (with the points) if you export save the cloud as an ASCII file.
You can change the colors/parameters of the currently displayed scalar field (see http://www.cloudcompare.org/doc/wiki/in ... properties and http://www.cloudcompare.org/doc/wiki/in ... es_Manager) to get a better visualization of what's happening in the part of interest. You can also extract the points below a given distance (or equivalently set a maximum distance when you compute the distances).
Otherwise you can also export all the values (with the points) if you export save the cloud as an ASCII file.
Daniel, CloudCompare admin