Discovering Structured Variations Via Template Matching

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

Research output: Contribution to journalArticlepeer-review

Abstract

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
Volume36
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • 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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