Matching Multiple 3D Reliefs

To digitalize human faces without occlusions, multiple depth maps have to be registered. After registration the scene has to be globally consistent. A straightforward method for aligning several 3D reliefs is pairwise matching, i.e., the new scan is registered against the scan with the largest overlapping areas. The latter one is determined in a preprocessing step. An alternative method is incremental matching, i.e., the new 3D relief is registered against a so called metascan, which is the union of the previous acquired and registered reliefs. Each scan matching has a limited precision. Both methods accumulate the registration errors such that the registration of many reliefs leads to inconsistent scenes[6].

Pulli presents a registration method that minimizes the global error and avoids inconsistent scenes[7]. Based on the idea of Pulli we designed a method called simultaneous matching. Hereby the first scan is the masterscan and determines the coordinate system. This scan is fixed. The following steps register all reliefs and minimize the global error:

1. Based on the prior knowledge about the relative coordinate systems, that needs not be precise or complete, pairwise matching is used to find a start registration for a new scan. This step speeds up computation.
2. A queue is initialized with the new scan.
3. Three steps are repeated until the queue is empty:
   1. The current scan is the first scan of the queue. This scan is removed from the queue.
   2. If the current scan is not the master scan, a set of neighbors (set of all reliefs which overlap with the current scan) is calculated. This set of neighbors form the point set $M$. The current scan forms the data point set $D$ and is aligned with the ICP algorithms.
   3. If the current scan changes its location by applying the transformation, then each single scan of the set of neighbors, which is not in the queue is added to the end of the queue.