  Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its
multi-iteration version, outperformed state of the art algorithms for local
point clouds registration. However, its performances have been tested using a
fixed high number of iterations. To be of practical usefulness, we think that
the algorithm should decide by itself when to stop, to avoid an excessive
number of iterations and, therefore, wasting computational time. With this
work, we compare different termination criterion on several datasets and prove
that the chosen one produce very good results that are comparable to those
obtained using a very high number of iterations while saving computational
time.
