| Title | Parameterisation invariant statistical shape models |
| Authors | Johan Karlsson, Anders Ericsson, Karl Åström |
| Alternative Location | http://dx.doi.org/10.1109/I..., Restricted Access |
| Publication | Proceedings of the 17th International Conference on Pattern Recognition |
| Year | 2004 |
| Pages | 23 - 26 |
| Document type | Conference paper |
| Conference name | Proceedings of the 17th International Conference on Pattern Recognition |
| Conference Date | 23-26 Aug. 2004 |
| Conference Location | Cambridge, UK |
| Status | Published |
| Quality controlled | Yes |
| Language | eng |
| Publisher | IEEE Comput. Soc |
| Abstract 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 |
| Keywords | automatic shape modelling, invariant statistical shape models, covariance matrix, curve parametrisations, |
| ISBN/ISSN/Other | ISBN: 0-7695-2128-2 |
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