Robust Range Image Registration Using Genetic Algorithms and the Surface Interpenetration Measure

- Provides a comprehensive review of the literature in range image registration and serves as an effective study guide on this important topic- Presents a novel robust error measure, the surface interpretation, which is easily computed and offers significant immunity to non-Gaussian errors. The shortcomings of the least squares formalism in this setting are carefully explored- The first substantive work focusing on precision alignment, and the first capable of attaining such alignments in low-overlap scenarios without human intervention or manual prealignment- Offers extensive experimental results, highlighting both the impact of robust measures, and the relative efficiency of genetic search algorithms versus more traditional approaches. Extensive comparisons with more traditional algorithms and measures are presented

Range Image Registration; Surface Interpenetration Measure (SIM); Range Image Registration using Genetic Algorithms; Robust Range Registration by Combining GAs and the SIM; Multiview Range Image Registration.