Discovering Structured Variations Via Template Matching

Duygu Ceylan, Minh Dang, Niloy J. Mitra, Boris Neubert, Mark Pauly

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We investigate this problem in the context of 3D acquisitions of buildings. Utilizing a set of template models, we discover geometric similarities across a set of building elements. Each template is equipped with a deformation model that defines variations of a base geometry. Central to our algorithm is a simultaneous template matching and deformation analysis that detects patterns across building elements by extracting similarities in the deformation modes of their matching templates. We demonstrate that such an analysis can successfully detect structured variations even for noisy and incomplete data.

Original languageEnglish (US)
Pages (from-to)76-88
Number of pages13
JournalComputer Graphics Forum
Issue number1
StatePublished - Jan 1 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 The Authors Computer Graphics Forum © 2016 The Eurographics Association and John Wiley & Sons Ltd.


  • I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling
  • shape analysis
  • template matching

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design


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