Update Quality Measurement authored by Cristina Cocho's avatar Cristina Cocho
...@@ -12,7 +12,8 @@ h (A, B) = \max_{a \in A} \{ \min_{b \in B} \{ d(a,b)\} \} \\[2mm] ...@@ -12,7 +12,8 @@ h (A, B) = \max_{a \in A} \{ \min_{b \in B} \{ d(a,b)\} \} \\[2mm]
Meshlab provides a Hausdorff distance calculation (a filter) so we decided to use it to calculate our quality parameter. For simplicity we used the python library Pymeshlab to automatize the quality calculation (see how to section for more details). Meshlab provides a Hausdorff distance calculation (a filter) so we decided to use it to calculate our quality parameter. For simplicity we used the python library Pymeshlab to automatize the quality calculation (see how to section for more details).
The Hausdorff filter provided by Pymeshlab basically selects a number of points a from the set A and searchs for each point a the closest point b of the set B. We can see how the result of the calculation depends strongly on the number of points used of the set A (which it will be called in the program the sampled mesh). It is a good criteria is to use as a number of sampling points the number of vertex of the sampling mesh (or higher). The Hausdorff filter provided by Pymeshlab basically selects a number of points a from the set A and searchs for each point a the closest point b of the set B. We can see how the result of the calculation depends strongly on the number of points used of the set A (which it will be called in the program the sampled mesh). It is a good criteria is to use as a number of sampling points the number of vertex of the sampling mesh (or higher).
Although both distances should be calculated, the most representative is the one whose sampling mesh has more density which it is normally the original mesh (in our case the original 3D model). Although both distances should be calculated, the most representative is the one whose sampling mesh has more density which it is normally the original mesh (in our case the original 3D model). More information about that can be found at: http://meshlabstuff.blogspot.com/2010/01/measuring-difference-between-two-meshes.html.
The Hausdorff filter from Pymeshlad provides the following values as a result: The Hausdorff filter from Pymeshlad provides the following values as a result:
- min: the minimum distance found between the two meshes - min: the minimum distance found between the two meshes
- max: the maximum distance found between the two meshes - max: the maximum distance found between the two meshes
...@@ -20,7 +21,7 @@ The Hausdorff filter from Pymeshlad provides the following values as a result: ...@@ -20,7 +21,7 @@ The Hausdorff filter from Pymeshlad provides the following values as a result:
- RMS: standard deviation. - RMS: standard deviation.
- diag_mesh_0: diagonal of the mesh 0 (sampling mesh) - diag_mesh_0: diagonal of the mesh 0 (sampling mesh)
- diag_mesh_1: diagonal of the mesh 1 (target mesh) - diag_mesh_1: diagonal of the mesh 1 (target mesh)
- n_samples: Number of samples used for sampling the sampling mesh - n_samples: number of samples used for sampling the sampling mesh
In general terms the two values that are going to be more useful when defining a quality criteria are max and mean. In general terms the two values that are going to be more useful when defining a quality criteria are max and mean.
On one side, the smaller value of max the closest are the two meshes so the better the descomposition has been. On one side, the smaller value of max the closest are the two meshes so the better the descomposition has been.
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