International audienceGiven a shape, a skeleton is a thin centered structure which jointly describes the topology and the geometry of the shape. Skeletons provide an alternative to classical boundary or volumetric representations, which is especially effective for applications where one needs to reason about, and manipulate, the structure of a shape. These skeleton properties make them powerful tools for many types of shape analysis and processing tasks. For a given shape, several skeleton types can be defined, each having its own properties, advantages, and drawbacks. Similarly, a large number of methods exist to compute a given skeleton type, each having its own requirements, advantages, and limitations. While using skeletons for two-dimensional (2D) shapes is a relatively well covered area, developments in the skeletonization of three-dimensional (3D) shapes make these tasks challenging for both researchers and practitioners. This survey presents an overview of 3D shape skeletonization. We start by presenting the definition and properties of various types of 3D skeletons. We propose a taxonomy of 3D skeletons which allows us to further analyze and compare them with respect to their properties. We next overview methods and techniques used to compute all described 3D skeleton types, and discuss their assumptions, advantages, and limitations. Finally, we describe several applications of 3D skeletons, which illustrate their added value for different shape analysis and processing tasks

International audienceMedial surfaces are well-known and interesting surface skeletons. As such, they can describe the topology and the geometry of a 3D closed object. Many applications in computer graphics can benefit from their properties, if we use them as Shape Representation Models (SRMs). However, visualizing the shape described by a medial surface remains a challenging problem. In this paper, we propose a method to build a mesh for any closed surface described by a medial surface. This method is based on the construction of an adaptive voxelisation from the geometry encoded with the medial surface. This discretization has the same topology as the described object, regardless its genus. Then, we mesh the boundary of this voxel-based representation to get a coarse approximation. Finally we refine this mesh using an original migration algorithm, in order to smooth the result and be as close as possible to the described object. An empirical study, on both CAO and laser scan models, shows the efficiency of our method in providing high quality surfaces with a reasonable computational complexity