We describe a convex relaxation for a family of problems of minimal perimeter partitions. The minimization of the relaxed problem can be tackled numerically, we describe an algorithm and show some results. In most cases, our relaxed problem finds a correct numerical approximation of the optimal solution: we give some arguments to explain why it should be so, and also discuss some situation where it fails. This preprint is a revised version of an technical paper of 2008 (see for instance the CMAP preprint #649, november 2008), which was rewritten in order to clarify, in particular, the relationship with the classical "paired calibration" approach for minimal surfaces
Robust fitting of geometric models is a core problem in computer vision. The most common approach is...
We consider surfaces which minimize a nonlocal perimeter functional and we discuss their interior re...
\u3cp\u3eLet P be a set of n points in the plane. We consider the problem of partitioning P into two...
We describe a convex relaxation for a family of problems of minimal perimeter partitions. The minimi...
We consider the Minimum Convex Partition problem: Given a set P of n points in the plane, draw a pla...
AbstractWe present a fixed-parameter algorithm for the Minimum Convex Partition and the Minimum Weig...
International audienceThis article provides numerical evidence that under volume constraint the ball...
Minimal partition problems consist in finding a partition of a domain into a given number of compone...
In this thesis we study different relaxations of non-convex functionals that can be found in image p...
Let P be a set of n points in the plane. We consider the problem of partitioning P into two subsets ...
This paper investigates a convex relaxation approach for minimum description length (MDL) based imag...
AbstractA convex partition with respect to a point set S is a planar subdivision whose vertices are ...
Abstract: In this paper we study the compact and convex sets K in the plane, that minimize the avera...
The Plateau problem consists of nding the set that minimizes its perimeter among all sets of a cer...
The problem of finding the convex hull of a set of points in the plane is one of the fundamental and...
Robust fitting of geometric models is a core problem in computer vision. The most common approach is...
We consider surfaces which minimize a nonlocal perimeter functional and we discuss their interior re...
\u3cp\u3eLet P be a set of n points in the plane. We consider the problem of partitioning P into two...
We describe a convex relaxation for a family of problems of minimal perimeter partitions. The minimi...
We consider the Minimum Convex Partition problem: Given a set P of n points in the plane, draw a pla...
AbstractWe present a fixed-parameter algorithm for the Minimum Convex Partition and the Minimum Weig...
International audienceThis article provides numerical evidence that under volume constraint the ball...
Minimal partition problems consist in finding a partition of a domain into a given number of compone...
In this thesis we study different relaxations of non-convex functionals that can be found in image p...
Let P be a set of n points in the plane. We consider the problem of partitioning P into two subsets ...
This paper investigates a convex relaxation approach for minimum description length (MDL) based imag...
AbstractA convex partition with respect to a point set S is a planar subdivision whose vertices are ...
Abstract: In this paper we study the compact and convex sets K in the plane, that minimize the avera...
The Plateau problem consists of nding the set that minimizes its perimeter among all sets of a cer...
The problem of finding the convex hull of a set of points in the plane is one of the fundamental and...
Robust fitting of geometric models is a core problem in computer vision. The most common approach is...
We consider surfaces which minimize a nonlocal perimeter functional and we discuss their interior re...
\u3cp\u3eLet P be a set of n points in the plane. We consider the problem of partitioning P into two...