Integrating prior shape models into level-set approaches

XM Pardo, V Leborán, R Dosil - Pattern Recognition Letters, 2004 - Elsevier
Pattern Recognition Letters, 2004Elsevier
To incorporate prior shape information into a deformable model either local or global shape
modeling must be carried out. Local shape modeling involves manual interaction to
accumulate information on the shape variability of any object. It depends on the existence of
homologous points, or landmarks, that must be unambiguously and consistently located in
different specimens. Global shape modeling does not require the existence of landmarks.
Global properties can be characterized using only a few parameters, and tend to be much …
To incorporate prior shape information into a deformable model either local or global shape modeling must be carried out. Local shape modeling involves manual interaction to accumulate information on the shape variability of any object. It depends on the existence of homologous points, or landmarks, that must be unambiguously and consistently located in different specimens. Global shape modeling does not require the existence of landmarks. Global properties can be characterized using only a few parameters, and tend to be much more stable than local properties. In this work we propose a new approach that combines the benefits of local and global shape modeling in the field of level-set approaches. The method starts with local shape parameterization, which eases user interaction. Then, the shape is converted into an implicit representation which exploits the stability and compactness of global shape parameters.
Elsevier
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