Strategies for registering range images from unknown camera positions

We describe a project to construct a 3D numerical model of Michelangelo's Florentine Pieta to be used in a study of the sculpture. Here we focus on the registration of the range images used to construct the model. The major challenge was the range of length scales involved. A resolution of 1 mm or less was required for the 2.25 m tall piece. To achieve this resolution, we could only acquire an area of 20 by 20 cm per scan. A total of approximately 700 range images were required. Ideally, a tracker would be attached to the scanner to record position and pose. The use of a tracker was not possible in the field. Instead, we used a crude-to-fine approach to registering the meshes to one another. The crudest level consisted of pairwise manual registration, aided by texture maps containing laser dots that were projected onto the sculpture. This crude alignment was refined by an automatic registration of laser dot centers. In this phase, we found that consistency constraints on dot matches were essential to obtaining accurate results. The laser dot alignment was further refined using a variation of the Iterated Closest Point (ICP) algorithm developed by Besl and McKay. In the application of ICP to global registration, we developed a method to avoid one class of local minima by finding a set of points, rather than the single point, that matches each candidate point.