Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
Optimization by Vector Space Methods
Optimization by Vector Space Methods
Geometry-Driven Diffusion in Computer Vision
Geometry-Driven Diffusion in Computer Vision
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Numerical Geometry of Images: Theory, Algorithms, and Applications
Numerical Geometry of Images: Theory, Algorithms, and Applications
Deformable Contour Method: A Constrained Optimization Approach
International Journal of Computer Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Journal of Mathematical Imaging and Vision
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Curve evolution forms the basis of active contour algorithms used for image segmentation. In many applications the curve under evolution needs to be restricted to the shape space given by some example shapes, or some linear space given by a set of basis vectors. Also, when a curve evolution is carried out on a computer, the evolution is approximated by some suitable discretization. Here too, the evolution is implicitly carried out in some subspace and not in the space of all curves. Hence it is important to study curve evolution in subspace of all curves. We look at a formulation that describes curve evolution restricted to subspaces. We give numerical methods and examples of a formulation for curvature flow for curves restricted to the B-spline subspace.