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Parameterisation invariant statistical shape models

In English

Författare

Summary, in English

In this paper novel theory to automate shape modelling is described. The main idea is to develop a theory that is intrinsically defined for curves, as opposed to a finite sample of points along the curves. The major problem here is to define shape variation in a way that is invariant to curve parametrisations. Instead of representing continuous curves using landmarks, the problem is treated analytically and numerical approximations are introduced at the latest stage. The problem is solved by calculating the covariance matrix of the shapes using a scalar product that is invariant to global reparametrisations. An algorithm for implementing the ideas is proposed and compared to a state of the an algorithm for automatic shape modelling. The problems with instability in earlier formulations are solved and the resulting models are of higher quality

Avdelning/ar

Publiceringsår

2004

Språk

Engelska

Sidor

23-26

Publikation/Tidskrift/Serie

Proceedings of the 17th International Conference on Pattern Recognition

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Mathematics

Nyckelord

  • automatic shape modelling
  • invariant statistical shape models
  • covariance matrix
  • curve parametrisations

Conference name

17th International Conference on Pattern Recognition, 2004

Conference date

2004-08-23 - 2004-08-26

Conference place

Cambridge, United Kingdom

Status

Published

ISBN/ISSN/Övrigt

  • ISBN: 0-7695-2128-2