The fields have the following meanings:
Subsampling rate for point clouds
Define the subsampling rate you want to use for matching. Since the data for the matching has
to be duplicated and processed, the additionally required memory very much depends on the
subsampling rate entered here. In addition, the parameter influences the computing time for
the matching.
Maximum search distance
This parameter defines the distance within which data from other measurements is considered
for the matching. Here, a value between 0.5 and 10.0 should be set. Higher values should only
be used in unfavorable cases. Typically the greater the search distance, the longer the time
needed for the calculation.
Note
To speed up the matching process, start with a large search distance (e.g. 10 mm) and a high
subsampling rate (e.g. 10). Then reduce the search distance (e.g. 2 mm) and the subsampling
rate (e.g. 2). Use this iterative method particularly when dealing with large data sets.
Maximum number of iterations
With this parameter, you determine how many iterations maximum are to be executed during
matching. If the convergence criterion described below is reached earlier, the matching is
stopped before the maximum number of iterations is reached.
Maximum allowable convergence
The convergence criterion defines the minimum distance by which a data set must be shifted
during an iteration so that the iteration is continued. The distance is set in millimeters.
Example: You have specified a convergence criterion of 0.0001 (0.1 micrometers). You match
10 data sets by global matching. The algorithm now tries to improve the position of each data
set. If at least one data set is moved by more than 0.0001 mm, another iteration is executed –
except if the maximum number of iterations has been reached.
