Using the Vector Distance Functions to Evolve Manifolds of Arbitrary Codimension

We present a novel method for representing and evolving objects of arbitrary dimension. The method, called the Vector Distance Function (VDF) method, uses the vector that connects any point in space to its closest point on the object. It can deal with smooth manifolds with and without boundaries and with shapes of different dimensions. It can be used to evolve such objects according to a variety of motions, including mean curvature. If discontinuous velocity fields are allowed the dimension of the objects can change. The evolution method that we propose guarantees that we stay in the class of VDF's and therefore that the intrinsic properties of the underlying shapes such as their dimension, curvatures can be read off easily from the VDF and its spatial derivatives at each time instant. The main disadvantage of the method is its redundancy: the size of the representation is always that of the ambient space even though the object we are representing may be of a much lower dimension. This disadvantage is also one of its strengths since it buys us flexibility.

[1]  Olivier D. Faugeras,et al.  Unfolding the Cerebral Cortex Using Level Set Methods , 1999, Scale-Space.

[2]  Yun-Gang Chen,et al.  Uniqueness and existence of viscosity solutions of generalized mean curvature flow equations , 1989 .

[3]  Joachim Weickert,et al.  Scale-Space Theories in Computer Vision , 1999, Lecture Notes in Computer Science.

[4]  J. Steinhoff,et al.  A New Eulerian Method for the Computation of Propagating Short Acoustic and Electromagnetic Pulses , 2000 .

[5]  Olivier Faugeras,et al.  Shape Representation as the Intersection of n-k Hypersurfaces , 2000 .

[6]  M. Gage,et al.  The heat equation shrinking convex plane curves , 1986 .

[7]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[8]  O. Faugeras,et al.  Representing and Evolving Smooth Manifolds of Arbitrary Dimension Embedded in Rn as the Intersection of n Hypersurfaces : The Vector Distance Functions , 1999 .

[9]  H. Soner,et al.  Level set approach to mean curvature flow in arbitrary codimension , 1996 .

[10]  W. D. Evans,et al.  PARTIAL DIFFERENTIAL EQUATIONS , 1941 .

[11]  M. Spivak A comprehensive introduction to differential geometry , 1979 .

[12]  Anthony J. Yezzi,et al.  Gradient flows and geometric active contour models , 1995, Proceedings of IEEE International Conference on Computer Vision.

[13]  I. Holopainen Riemannian Geometry , 1927, Nature.

[14]  Guillermo Sapiro,et al.  Region Tracking on Surfaces Deforming via Level-Sets Methods , 1999, Scale-Space.

[15]  M. Grayson The heat equation shrinks embedded plane curves to round points , 1987 .

[16]  Jack Xin,et al.  Diffusion-Generated Motion by Mean Curvature for Filaments , 2001, J. Nonlinear Sci..

[17]  Vladimir Igorevich Arnold,et al.  Geometrical Methods in the Theory of Ordinary Differential Equations , 1983 .

[18]  Luigi Ambrosio,et al.  Curvature and distance function from a manifold , 1998 .

[19]  S. Osher,et al.  Motion of curves in three spatial dimensions using a level set approach , 2001 .