Title:
Algorithms for stochastic approximations of curvature flows
Algorithms for stochastic approximations of curvature flows
Author(s)
Unal, Gozde
Nain, Delphine
Ben Arous, Gérard
Shimkin, Nahum
Tannenbaum, Allen R.
Zeitouni, Ofer
Nain, Delphine
Ben Arous, Gérard
Shimkin, Nahum
Tannenbaum, Allen R.
Zeitouni, Ofer
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Abstract
Curvature flows have been extensively considered from a deterministic point of view. They have been shown to be useful for a number of applications including crystal growth, flame propagation, and computer vision. In some previous work G. Ben-Arous et al. (2002), we have described a random particle system, evolving on the discretized unit circle, whose profile converges toward the Gauss-Minkowsky transformation of solutions of curve shortening flows initiated by convex curves. The present note shows that this theory may be implemented as a new way of evolving curves and as a possible alternative to level set methods.
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2003-09
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Proceedings