Robust 3D object registration based on pairwise matching of geometric distributions

With the advent of 3D digital libraries and 3D shape retrieval engines, 3D shape representation has been receiving major attention because of its vital role in such systems. In this framework, establishing a representation that allows effective matching and alignment between shapes is a key and fundamental requirement. In this paper, we present a novel representation for arbitrary surfaces that enables local correspondences to be determined. We then describe how these local correspondences can be used to search for the transformation that best aligns all surface data. If this transformation is found to align a significant proportion of the surface data, then the surfaces are said to have a correspondence. Experiments conducted on various objects confirmed the effectiveness of our approach and its robustness with respect to corrupted and missing data.