The Lux scanners provide a cloud of scan points, which
must be processed to extract the essential features. Ideally, all
points that belong to the same object in the real world are
brought into a single cluster. For this purpose, we apply a
simple distance-based cluster heuristic. As [3] suggests, this
is improved by feeding back strong hypotheses of the fusion
module back to the clustering phase.