Abstract. TVLA is a parametric framework for shape analysis that can be easily instantiated to create different kinds of analyzers for checking properties of programs that use link...
Igor Bogudlov, Tal Lev-Ami, Thomas W. Reps, Mooly ...
The level set representation of shapes is useful for shape evolution and is widely used for the minimization of energies with respect to shapes. Many algorithms consider energies d...
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...
We propose a level set based variational approach that incorporates shape priors into Chan-Vese's model [3] for the shape prior segmentation problem. In our model, besides th...
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum