An affine invariant deformable shape representation for general curves

Anders Ericsson, Karl Åström

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingResearchpeer-review

12 Citations (SciVal)

Abstract

Automatic construction of Shape Models from examples has been the focus of intense research during the last couple of years. These methods have proved to be useful for shape segmentation, tracking and shape understanding. In this paper novel theory to automate shape modelling is described. The theory is intrinsically defined for curves although curves are infinite dimensional objects. The theory is independent of parameterisation and affine transformations. We suggest a method for implementing the ideas and compare it to minimising the Description Length of the model (MDL). It turns out that the accuracy of the two methods is comparable. Both the MDL and our approach can get Stuck at local minima. Our algorithm is less computational expensive and relatively good solutions are obtained after a few iterations. The MDL is, however, better suited at fine-tuning the parameters given good initial estimates to the problem. It is shown that a combination of the two methods outperforms either on its own.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Computer Vision
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages1142-1149
Volume2
ISBN (Print)0-7695-1950-4
DOIs
Publication statusPublished - 2003
Event9th International Conference on Computer Vision, IEEE - Nice, France
Duration: 2003 Oct 132003 Oct 16

Publication series

Name
Volume2

Conference

Conference9th International Conference on Computer Vision, IEEE
Country/TerritoryFrance
CityNice
Period2003/10/132003/10/16

Subject classification (UKÄ)

  • Mathematics

Keywords

  • Affine invariant deformable shape representation
  • Description length of the model
  • Shape variation

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