@@ -128,7 +128,15 @@ The parameters convexHullDownsampling and planeDownsampling have a small influen
The influence of the alpha and beta parameters is also interesting to analyse.
We can see how bigger values of beta lead to a higher decomposition. The beta parameter is used to give (or remove) weight to the symmetry factor: the bigger it is, the more chances we have to use as a clipping plane a plane orthogonal to a revolution axis (leading to a two subsets of voxels with similar or identical shape). As our model studied, the cup, has a revolution axis (with the exception of the handle), the increase of the beta parameter produces an increase of the pieces obtained after the decomposition. This effect will probably not happen if the model has not a revolution axis.
However, even if we have more number of pieces the decomposition is not correct, we can see how in our case big values of the beta parameter produce a poor/bad decomposition of the cup handle (it is considered to be one piece - its hole is filled).
However, even if we have more number of pieces the decomposition is not correct, we can see how in our case big values of the beta parameter produce a poor/bad decomposition of the cup handle (it is considered to be one piece - its hole is filled). This effect is shown in the following screenshots:
If we focus on the alpha parameter we can see how, in our tests, big values of it produce higher number of pieces. As with the beta parameter, this is probably due to the fact that our model is quite symmetric so that the volumes of the subsets of voxels obtained after clipping are quite close (remember the alpha is the factor that goes with the balance component of the energy criteria). This behaviour will probably not occur when the model is less symmetric. A use of a higher value of the alpha parameter (higher than ten default value) could be used in order to have a bigger decomposition, tests have not shown the same bad effects we had when increased the beta parameter.
