Boat’s hull modeling with low cost triangulation scanners

In a 3D acquisition project range maps collected around the object to be modeled, need to be integrated. With portable range cameras these range maps are taken from unknown positions and their coordinate systems are local to the sensor. The problem of unifying all the measurements in a single reference system is solved by taking contiguous range maps with a suitable overlap level; taking one map as reference and doing a rototranslation of the adjacent ones by using an "Iterative Closest Point" (ICP) method. Depending on the 3D features over the acquired surface and on the amount of overlapping, the ICP algorithm convergence can be more or less satisfactory. Anyway it always has a random component depending on measurement uncertainty. Therefore, although each individual scan has a very good accuracy, the error's propagation may produce deviations in the aligned set respect to real surface points. In this paper a systematic study of the different alignment modality and the consequent total metric distortions on the final model, is shown. In order to experiment these techniques a case-study of industrial interest was chosen: the 3D modeling of a boat's hull mold. The experiments involved a triangulation based laser scanner integrated with a digital photogrammetry system. In order to check different alignment procedures, a Laser Radar capable to scan all the object surface with a single highly accurate scan, was used to create a "gold-standard" data set. All the experiments were compared with this reference and from the comparison several interesting methodological conclusions have been obtained.