57 PCL_ERROR (
"[pcl::%s::initCompute] Init failed.\n", getClassName ().
c_str ());
61 if (search_radius_< min_radius_)
63 PCL_ERROR (
"[pcl::%s::initCompute] search_radius_ must be GREATER than min_radius_.\n", getClassName ().
c_str ());
68 descriptor_length_ = elevation_bins_ * azimuth_bins_ * radius_bins_;
75 radii_interval_.clear ();
76 phi_divisions_.clear ();
77 theta_divisions_.clear ();
81 radii_interval_.resize (radius_bins_ + 1);
82 for (std::size_t j = 0; j < radius_bins_ + 1; j++)
83 radii_interval_[j] =
static_cast<float> (std::exp (std::log (min_radius_) + ((
static_cast<float> (j) /
static_cast<float> (radius_bins_)) * std::log (search_radius_ / min_radius_))));
87 theta_divisions_[0] = 0.f;
88 std::partial_sum(theta_divisions_.begin (), theta_divisions_.end (), theta_divisions_.begin ());
92 phi_divisions_[0] = 0.f;
93 std::partial_sum(phi_divisions_.begin (), phi_divisions_.end (), phi_divisions_.begin ());
100 float e = 1.0f / 3.0f;
102 volume_lut_.resize (radius_bins_ * elevation_bins_ * azimuth_bins_);
104 for (std::size_t j = 0; j < radius_bins_; j++)
107 float integr_r = (radii_interval_[j+1] * radii_interval_[j+1] * radii_interval_[j+1] / 3.0f) - (radii_interval_[j] * radii_interval_[j] * radii_interval_[j] / 3.0f);
109 for (std::size_t k = 0; k < elevation_bins_; k++)
120 for (std::size_t l = 0; l < azimuth_bins_; l++)
124 volume_lut_[(l*elevation_bins_*radius_bins_) + k*radius_bins_ + j] = 1.0f /
powf (
V,
e);
137 Eigen::Map<Eigen::Vector3f> x_axis (rf);
138 Eigen::Map<Eigen::Vector3f> y_axis (rf + 3);
139 Eigen::Map<Eigen::Vector3f> normal (rf + 6);
147 std::fill (desc.begin (), desc.end (), std::numeric_limits<float>::quiet_NaN ());
148 std::fill (rf, rf + 9, 0.f);
159 normal = normals[
minIndex].getNormalVector3fMap ();
166 x_axis[2] = - (normal[0]*x_axis[0] + normal[1]*x_axis[1]) / normal[2];
168 x_axis[1] = - (normal[0]*x_axis[0] + normal[2]*x_axis[2]) / normal[1];
170 x_axis[0] = - (normal[1]*x_axis[1] + normal[2]*x_axis[2]) / normal[0];
178 y_axis.matrix () = normal.cross (x_axis);
193 Eigen::Vector3f
proj;
201 Eigen::Vector3f cross = x_axis.cross (
proj);
203 phi = cross.dot (normal) < 0.f ? (360.0f -
phi) :
phi;
211 const auto rad_min = std::lower_bound(std::next (radii_interval_.cbegin ()), radii_interval_.cend (), r);
212 const auto theta_min = std::lower_bound(std::next (theta_divisions_.cbegin ()), theta_divisions_.cend (),
theta);
213 const auto phi_min = std::lower_bound(std::next (phi_divisions_.cbegin ()), phi_divisions_.cend (),
phi);
216 const auto j = std::distance(radii_interval_.cbegin (), std::prev(
rad_min));
217 const auto k = std::distance(theta_divisions_.cbegin (), std::prev(
theta_min));
218 const auto l = std::distance(phi_divisions_.cbegin (), std::prev(
phi_min));
229 volume_lut_[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j];
232 if (w == std::numeric_limits<float>::infinity ())
233 PCL_ERROR (
"Shape Context Error INF!\n");
235 PCL_ERROR (
"Shape Context Error IND!\n");
237 desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] += w;
239 assert (desc[(l*elevation_bins_*radius_bins_) + (k*radius_bins_) + j] >= 0);
243 std::fill (rf, rf + 9, 0);
bool computePoint(std::size_t index, const pcl::PointCloud< PointNT > &normals, float rf[9], std::vector< float > &desc)
Estimate a descriptor for a given point.
bool initCompute() override
Initialize computation by allocating all the intervals and the volume lookup table.
typename Feature< PointInT, PointOutT >::PointCloudOut PointCloudOut
void computeFeature(PointCloudOut &output) override
Estimate the actual feature.
bool equal(T val1, T val2, T eps=std::numeric_limits< T >::min())
Check if val1 and val2 are equal to an epsilon extent.