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// This file is part of libigl, a simple c++ geometry processing library.
//
// Copyright (C) 2013 Alec Jacobson <alecjacobson@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla Public License
// v. 2.0. If a copy of the MPL was not distributed with this file, You can
// obtain one at http://mozilla.org/MPL/2.0/.
#ifndef IGL_UNIFORMLY_SAMPLE_TWO_MANIFOLD_H
#define IGL_UNIFORMLY_SAMPLE_TWO_MANIFOLD_H
#include "igl_inline.h"
#include <Eigen/Dense>
namespace igl
{
// UNIFORMLY_SAMPLE_TWO_MANIFOLD Attempt to sample a mesh uniformly with
// k-points by furthest point relaxation as described in "Fast Automatic
// Skinning Transformations" [Jacobson et al. 12] Section 3.3. The input is
// not expected to be a typical 3D triangle mesh (e.g., [V,F]), instead each
// vertex is embedded in a high dimensional unit-hypercude ("weight space")
// defined by W, with triangles given by F. This algorithm will first conduct
// furthest point sampling from the set of vertices and then attempt to relax
// the sampled points along the surface of the high-dimensional triangle mesh
// (i.e., the output points may be in the middle of triangles, not just at
// vertices). An additional "push" factor will repel samples away from the
// corners of the hypercube.
//
// Inputs:
// W #W by dim positions of mesh in weight space
// F #F by 3 indices of triangles
// k number of samples
// push factor by which corners should be pushed away
// Outputs
// WS k by dim locations in weight space
//
// See also:
// random_points_on_mesh
//
IGL_INLINE void uniformly_sample_two_manifold(
const Eigen::MatrixXd & W,
const Eigen::MatrixXi & F,
const int k,
const double push,
Eigen::MatrixXd & WS);
// Find uniform sampling up to placing samples on mesh vertices
IGL_INLINE void uniformly_sample_two_manifold_at_vertices(
const Eigen::MatrixXd & OW,
const int k,
const double push,
Eigen::VectorXi & S);
}
#ifndef IGL_STATIC_LIBRARY
# include "uniformly_sample_two_manifold.cpp"
#endif
#endif