I have two meshes. Low resolution and a high resolution one. High resolution
mesh is just a part of the Low res. mesh. Computation of the Hausdorff
distance doesn't work (0 samples), could you explain me the problem please?
Could I perform distance computation somehow between the mesh and it's aligned
part?
thank you.
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I also tried to apply Hausdorff distance to two identical meshes, one mesh was
shifted (one can see it visually). This time there were sampled points, but
the result was strange:
Filter: Hausdorff Distance computed
Filter: Sample 43140
Filter: min : 0.000000 max 0.000000
Filter: mean : 0.000000 RMS : 0.000000
Filter: Values w.r.t. BBox Diag (157.584946)
Filter: min : 0.000000 max 0.000000
Filter: mean : 0.000000 RMS : 0.000000
I use MeshLab v1.2.3 revision: 4312, vcg revision: 3752.
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I found a mistake for these errors. Before you apply Hausdorff distance
filter, you need to freeze all the matrix (of course if you did any
transformations before)!
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Hello,
I have two meshes. Low resolution and a high resolution one. High resolution
mesh is just a part of the Low res. mesh. Computation of the Hausdorff
distance doesn't work (0 samples), could you explain me the problem please?
Could I perform distance computation somehow between the mesh and it's aligned
part?
thank you.
I also tried to apply Hausdorff distance to two identical meshes, one mesh was
shifted (one can see it visually). This time there were sampled points, but
the result was strange:
Filter: Hausdorff Distance computed
Filter: Sample 43140
Filter: min : 0.000000 max 0.000000
Filter: mean : 0.000000 RMS : 0.000000
Filter: Values w.r.t. BBox Diag (157.584946)
Filter: min : 0.000000 max 0.000000
Filter: mean : 0.000000 RMS : 0.000000
I use MeshLab v1.2.3 revision: 4312, vcg revision: 3752.
I found a mistake for these errors. Before you apply Hausdorff distance
filter, you need to freeze all the matrix (of course if you did any
transformations before)!
Thanks for the tip!