
namespace CGAL {
/*!

\mainpage User Manual 
\anchor Chapter_dD_Convex_Hulls_and_Delaunay_Triangulations
\anchor chapconvexhulld
\authors Susan Hert and Michael Seel

\deprecated This package is deprecated since the version 4.6 of \cgal. The package \ref PkgTriangulations should be used instead.

\section Convex_hull_dIntroduction Introduction

A subset \f$ S \subseteq \mathbb{R}^d\f$ is convex if for any two points \f$ p\f$ and \f$ q\f$
in the set the line segment with endpoints \f$ p\f$ and \f$ q\f$ is contained
in \f$ S\f$. The convex hull of a set \f$ S\f$
is the smallest convex set containing
\f$ S\f$. The convex hull of a set of points \f$ P\f$ is a convex
polytope with vertices in \f$ P\f$. A point in \f$ P\f$ is an extreme point
(with respect to \f$ P\f$) if it is a vertex of
the convex hull of \f$ P\f$. A set of points is said to be strongly convex if it consist of only extreme points.

This chapter describes the class provided in \cgal for producing convex 
hull in arbitrary dimensions. There is an intimate relationship between 
the Delaunay triangulation of a point set \f$ S\f$ and the convex hull of 
`lift(S)`: The nearest site
Delaunay triangulation is the projection of the lower hull and the
furthest site Delaunay triangulation is the upper hull. Here we also 
describe the companion class to the convex hull class that computes 
nearest and furthest site Delaunay triangulations.

\section Convex_hull_ddD dD Convex Hull

The class `Convex_hull_d<R>` is used to represent the
convex hull of a set of points in \f$ d\f$-dimensional space. This class
supports incremental construction of hulls, and provides a rich
interface for exploration. There are also output routines for hulls
of dimension 2 and 3.

The convex hull class is parameterized by a traits class that provides 
\f$ d\f$-dimensional data types and predicates. The class 
`Convex_hull_d_traits_3` adapts any low-dimensional standard kernel 
model <I>e.g.</I>, `Homogeneous<RT>` or `Cartesian<FT>` for use 
with `Convex_hull_d`, where the dimension is fixed to three.
The validity of the computed convex hull can be checked using the
member function `Convex_hull_d::is_valid`, which implements the algorithm
of Mehlhorn <I>et al.</I>\cgalCite{mnssssu-cgpvg-96} to determine if
the vertices of a given polytope constitute a strongly convex point
set or not.

The implementation follows the papers \cgalCite{cms-frric-93} and
\cgalCite{bms-dgc-94}.

\section Convex_hull_dDelaunay Delaunay Triangulation

There is a class type with a thorough interface providing the
construction and exploration of closest and furthest site Delaunay
simplicial complexes in arbitrary higher dimension. The class
`Delaunay_d<R, Lifted_R>`C provides an
implementation via the lifting map to higher dimensional
convex hulls.lifting map, dD.
The class supports incremental construction of Delaunay triangulations 
and various kind of query operations (in particular, nearest and furthest
neighbor queries and range queries with spheres and simplices).

*/ 
} /* namespace CGAL */

