Fig 2. Registration errors for registering a mesh target shape. (Experiment 2).

Source shapes were randomly generated from a mesh model of a human hip (Fig. 1A), misaligned by (A): [15, 30] mm / degrees and (B): [30, 60] mm / degrees, and registered back to the mesh. The test cases represent the different noise models used to generate noise on the source shape (Table 4). For each test case, 300 randomized trials were conducted, with successful registrations being used to compute an average target registration error (TRE). The error bars provide approximate standard deviations of the reported average TRE values. The proposed IMLP algorithm was evaluated relative to standard ICP [1] and relative to near-comparisons of GTLS-ICP [10] and A-ICP [12] using IMLP-CP and IMLP-MD, which modify IMLP’s most-likely match criteria to that of closest-point and Mahalanobis-distance matching, respectively.