Hello Mr. Daniel,
I sincerely appreciate your ongoing support on this platform.
Currently, I'm immersed in my research project where I aim to compare two meshes, both exhibiting a cylindrical shape. During my exploration, while examining the C2M signed distances for one sample, I noticed that the points at the lowest section of the control mesh hover around 0.6 mm (despite the distance between these points in the control and reference meshes in this bottom area being approximately 3mm - figures 1 and 2). Moreover, in another comparison, the points register a value closer to 0.7 units (although the distance between corresponding points in the control and reference meshes at the bottom area is around 5mm - figures 3 and 4).
I recall your earlier explanation that C2M operates by measuring the distances between the closest points. Thus, in scenarios like this, the points at the base of the control mesh are juxtaposed with points from the reference mesh situated in the periphery at a similar level, rather than directly with the lowest points of the reference mesh. Am I understanding this correctly?
Essentially, what I aim to achieve through this comparison is to ascertain the deviation across all meshes and to ensure that I'm comparing points located at equivalent positions in both the control and reference meshes. Could you provide guidance on how I can accomplish this?
My ultimate goal is to document how altering the depth of the scanned object impacts the accuracy of the scanner. I suspect that relying solely on the RMS generated through the C2M distances might underestimate the overall discrepancy, what do you think?
Interpretation of C2M signed distances when the distance between points is great
Interpretation of C2M signed distances when the distance between points is great
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- figure 1 - C2M signed distances.png (235.77 KiB) Viewed 220 times
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- figure 2 - C2M signed distances with the reference vertices.png (353.86 KiB) Viewed 220 times
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- figure 3 - C2M signed distances.png (198.92 KiB) Viewed 220 times
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- figure 4 - C2M signed distances with the reference vertices.png (283.75 KiB) Viewed 220 times
Re: Interpretation of C2M signed distances when the distance between points is great
Can you send me these meshes so that I can double check things on my side? (the new version of CC is more robust, so the C2M distances should not have the same issue as before with 'flipped' distances, but I don't see why the reported distances would be much larger than what you expect...).
And adding the maximum distance can also be interesting, but sadly it's highly dependent on the noise... So not super robust.
In the end the RMS, or equivalently the standard deviation, are probably the best indicator AFAIK.
Can you clarify what you are referring to by 'equivalent' positions? Because the issue is that neither the vertices of the mesh, nor the points sampled on the mesh will be exactly at the same position. You are kind of bound to use a statistical approach. I believe that using a sampling of points with a controlled surface density (the second option when using 'Edit > Mesh > Sample points') will be the best option in this case. I mean sampling points on the compared entity with a controlled density, and comparing the resulting cloud to the reference mesh.Essentially, what I aim to achieve through this comparison is to ascertain the deviation across all meshes and to ensure that I'm comparing points located at equivalent positions in both the control and reference meshes. Could you provide guidance on how I can accomplish this?
You can of course compare the average distance if you want to detect a potential shift. But that depends on how the different datasets are registered together (if it's with ICP or a similar approach, the average distance should always be close to zero, as these techniques will suppress the shift/bias).My ultimate goal is to document how altering the depth of the scanned object impacts the accuracy of the scanner. I suspect that relying solely on the RMS generated through the C2M distances might underestimate the overall discrepancy, what do you think?
And adding the maximum distance can also be interesting, but sadly it's highly dependent on the noise... So not super robust.
In the end the RMS, or equivalently the standard deviation, are probably the best indicator AFAIK.
Daniel, CloudCompare admin