Abstract
Building on recent work by others who introduced RBFs into level
sets for structural topology optimisation, we introduce the concept
into active models and present a new level set formulation able to
handle more complex topological changes, in particular perturbation
away from the evolving front. This allows the initial contour
or surface to be placed arbitrarily in the image. The proposed level
set updating scheme is efficient and does not suffer from
self-flattening while evolving, hence it avoids large numerical
errors. Unlike conventional level set based active models, periodic
re-initialisation is also no longer necessary and the computational
grid can be much coarser, thus, it has great potential in modelling
in high dimensional space. We show results on synthetic and real
data for active modelling in 2D and 3D.
Translated title of the contribution | Implicit Active Model using Radial Basis Function Interpolated Level Sets |
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Original language | English |
Title of host publication | Proceedings of the 18th British Machine Vision Conference |
Publisher | BMVA Press |
Publication status | Published - 2007 |
Bibliographical note
Other page information: 1040-1049Conference Proceedings/Title of Journal: Proceedings of the 18th British Machine Vision Conference
Other identifier: 2000752