in: Research in Shape Analysis, Aslı Gençtav,Kathryn Leonard,Sibel Tari,Evelyne Hubert,Geraldine Morin,Noha El-Zehiry, Editor, Springer, Cham, Zug, pp.95-109, 2018
Using level sets of a pair of transformations, we adaptively bring two shapes to be matched to a comparable topology prior to a correspondence search. One of the transformations readily provides a central structure for each shape. We utilize the central structure as a reference volume for scale normalization. By adaptively dilating the central structure with the help of the second transformation, we construct what we refer to as the barrier structure. The barrier structure is used to automatically stop topology equating adaptive deflations. Illustrative experiments using different datasets demonstrate that our approach provides robust solutions for the topological noise caused by localized touches or spurious links that connect different shape parts.