Coarse-to-Fine Matching of Shapes Using Disconnected Skeletons by Learning Class-Specific Boundary Deformations

Erdem A., TARI Z. S.

7th International Workshop on Graph-Based Representations in Pattern Recognition, Venice, Italy, 26 - 28 May 2009, vol.5534, pp.21-22 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 5534
  • City: Venice
  • Country: Italy
  • Page Numbers: pp.21-22
  • Middle East Technical University Affiliated: Yes


Disconnected skeleton [1] is a very coarse yet a very stable skeleton-based representation scheme for generic shape recognition in which recognition is performed mainly based on the structure of disconnection points of extracted branches, without explicitly using information about boundary details [2,3]. However, sometimes sensitivity to boundary details may be required in order to achieve the goal of recognition. In this study, we first present a simple way to enrich disconnected skeletons with radius functions. Next, we attempt to resolve the conflicting goals of stability and sensitivity by proposing a coarse-to-fine shape matching algorithm. As the first step, two shapes are matched based oil the structure of their disconnected skeletons. and following to that the computed matching cost is re-evaluated by taking into account the similarity of boundary details in the light of class-specific boundary deformations which are learned from a given set of examples.