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longer description 

rename file
This commit is contained in:
pierre alliez 2015-02-13 22:14:15 +01:00
parent b78a6a2d16
commit f3721a8778
3 changed files with 9 additions and 7 deletions
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6
Point_set_shape_detection_3/examples/Point_set_shape_detection_3/shape_detection_3_minimal_planar_shape.h → Point_set_shape_detection_3/examples/Point_set_shape_detection_3/shape_detection_3_custom_shape.h
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@ -8,7 +8,7 @@
*/
namespace CGAL {
/*!
\brief My_Plane implements Shape_base. The plane is parameterized by the normal vector and the distance to the origin.
\brief My_Plane derives from Shape_base. The plane is parameterized by the normal vector and the distance to the origin.
*/
template <class Sd_traits>
class My_Plane : public Shape_base<Sd_traits> {
@ -67,8 +67,8 @@ namespace CGAL {
std::string info() const {
std::stringstream sstr;
sstr << "Type: plane (" << m_normal.x() << ", "
<< m_normal.y() << ", "
<< m_normal.z() << ")x - " << m_d << " = 0" << " #Pts: " << this->m_indices.size();
<< m_normal.y() << ", "
<< m_normal.z() << ")x - " << m_d << " = 0" << " #Pts: " << this->m_indices.size();
return sstr.str();
}

2
Point_set_shape_detection_3/package_info/Point_set_shape_detection_3/description.txt
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@ -1,3 +1,3 @@
Point Set Shape Detection
This CGAL package implements a RANSAC method for detecting shapes in an unorganized point set with unoriented normals.
This CGAL package implements an efficient RANSAC approach for detecting shapes in an unorganized point set with unoriented normals.

8
Point_set_shape_detection_3/package_info/Point_set_shape_detection_3/long_description.txt
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@ -1,5 +1,7 @@
Point Set Shape Detection
Point Set Shape Detection
Sven Oesau, Yannick Verdie and Clément Jamin
Sven Oesau, Yannick Verdie, Clément Jamin and Pierre Alliez
This CGAL package implements a RANSAC (random sample consensus) method for detecting shapes in a point set with unoriented normals. The available shapes for detection are planes, spheres, cylinders, cones and tori.
This CGAL package implements an efficient RANSAC (random sample consensus) approach for detecting shapes in a point set with unoriented normals.
Five canonical shapes can be detected: planes, spheres, cylinders, cones and tori.
Additional shapes can be detected, provided a class derived from the base shape is implemented.