Evaluating a method for automated rigid registration

We evaluate a novel method for fully automated rigid registration of 2D manifolds in 3D space based on distance maps, the Gibbs sampler and Iterated Conditional Modes (ICM). The method is tested against the ICP considered as the gold standard for automated rigid registration. Furthermore, the influence of different norms and sampling point densities is evaluated. The performance of the two methods has been evaluated on data consisting of 178 scanned ear impressions taken from the right ear. To quantify the difference of the two methods we calculate the registration cost and the mean point to point distance. T-test for common mean are used to determine the performance of the two methods (supported by a Wilcoxon signed rank test). The performance influence of sampling density, sampling quantity, and norms is analyzed using a similar method.