Two-stage automated measurement process for high-resolution 3D digitization of unknown objects.

In this paper, a process for high-resolution, automated 3D digitization of unknown objects (i.e., without any digital model) is presented. The process has two stages-the first leads to a coarse 3D digital model of the object, and the second obtains the final model. A rough model, acquired by a 3D measurement head with a large working volume and relatively low resolution, is used to calculate the precise head positions required for the full digitization of the object, as well as collision detection and avoidance. We show that this approach is much more efficient than digitization with only a precise head, when its positions for subsequent measurements (so-called next-best-views) must be calculated based only on a partially recovered 3D model of the object. We also show how using a rough object representation for collision detection shortens the high-resolution digitization process.