International audienceWe introduce a parameterized notion of feature size that interpolates between the minimum of the local feature size and the recently introduced weak feature size. Based on this notion of feature size, we propose sampling conditions that apply to noisy samplings of general compact sets in euclidean space. These conditions are sufficient to ensure the topological correctness of a reconstruction given by an offset of the sampling. Our approach also yields new stability results for medial axes, critical points, and critical values of distance functions
AbstractReconstructing a 3D shape from sample points is a central problem faced in medical applicati...
This thesis deals with the general question of geometric inference. Given an object that is only kno...
International audienceData often comes in the form of a point cloud sampled from an unknown compact ...
We introduce a parameterized notion of feature size that in-terpolates between the minimum of the lo...
AbstractThis work addresses the problem of the approximation of the normals of the offsets of genera...
International audienceGiven a smooth compact codimension one submanifold S of Rk and a compact appro...
AbstractGiven a smooth compact codimension one submanifold S of Rk and a compact approximation K of ...
In this paper 1, we use the framework of distance functions to study some geometric and topological ...
International audienceReconstructing a 3D shape from sample points is a central problem faced in med...
International audienceIn this work one proves that under quite general assumptions one can deduce th...
We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an as...
Often noisy point clouds are given as an approximation of a particular compact set of interest. A fi...
Data often comes in the form of a point cloud sampled from an unknown compact subset of Euclidean sp...
International audienceThis work is closely related to the theories of set estimation and manifold es...
Abstract: We develop algorithms for sampling from a probability distribution on a submanifold embedd...
AbstractReconstructing a 3D shape from sample points is a central problem faced in medical applicati...
This thesis deals with the general question of geometric inference. Given an object that is only kno...
International audienceData often comes in the form of a point cloud sampled from an unknown compact ...
We introduce a parameterized notion of feature size that in-terpolates between the minimum of the lo...
AbstractThis work addresses the problem of the approximation of the normals of the offsets of genera...
International audienceGiven a smooth compact codimension one submanifold S of Rk and a compact appro...
AbstractGiven a smooth compact codimension one submanifold S of Rk and a compact approximation K of ...
In this paper 1, we use the framework of distance functions to study some geometric and topological ...
International audienceReconstructing a 3D shape from sample points is a central problem faced in med...
International audienceIn this work one proves that under quite general assumptions one can deduce th...
We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an as...
Often noisy point clouds are given as an approximation of a particular compact set of interest. A fi...
Data often comes in the form of a point cloud sampled from an unknown compact subset of Euclidean sp...
International audienceThis work is closely related to the theories of set estimation and manifold es...
Abstract: We develop algorithms for sampling from a probability distribution on a submanifold embedd...
AbstractReconstructing a 3D shape from sample points is a central problem faced in medical applicati...
This thesis deals with the general question of geometric inference. Given an object that is only kno...
International audienceData often comes in the form of a point cloud sampled from an unknown compact ...