This paper tackles an important aspect of the variational problem underlying active contours: optimization by gradient flows.
Classically, the definition of a gradient depends directly on the choice of an inner product structure. This consideration
is largely absent from the active contours literature. Most authors, explicitely or implicitely, assume that the space of
admissible deformations is ruled by the canonical
L
2 inner product. The classical gradient flows reported in the literature are relative to this particular choice. Here, we investigate
the relevance of using (i) other inner products, yielding other gradient descents, and (ii) other minimizing flows not deriving
from any inner product. In particular, we show how to induce different degrees of spatial consistency into the minimizing
flow, in order to decrease the probability of getting trapped into irrelevant local minima. We report numerical experiments
indicating that the sensitivity of the active contours method to initial conditions, which seriously limits its applicability
and efficiency, is alleviated by our application-specific spatially coherent minimizing flows. We show that the choice of
the inner product can be seen as a prior on the deformation fields and we present an extension of the definition of the gradient
toward more general priors.
Keywords shape - gradient descent - active contours - minimization flow - inner product - sobolev - generalized gradient - rigidification - semi-local rigidification - shape warping - landmarks - Hausdorff distance - spatial coherence