template<typename PointT, typename LeafT, typename BranchT, typename OctreeT> void
pcl::octree::OctreePointCloud<PointT, LeafT, BranchT, OctreeT>::addPointFromCloud (const int pointIdx_arg, IndicesPtr indices_arg)
{
this->addPointIdx (pointIdx_arg);
if (indices_arg)
indices_arg->push_back (pointIdx_arg);
}
template <typename PointT> void
pcl::StatisticalMultiscaleInterestRegionExtraction<PointT>::extractExtrema (std::list<IndicesPtr> &rois)
{
std::vector<std::vector<bool> > is_min (scale_values_.size ()),
is_max (scale_values_.size ());
// for each point, check if it is a local extrema on each scale
for (size_t scale_i = 0; scale_i < scale_values_.size (); ++scale_i)
{
std::vector<bool> is_min_scale (input_->points.size ()),
is_max_scale (input_->points.size ());
for (size_t point_i = 0; point_i < input_->points.size (); ++point_i)
{
std::vector<int> nn_indices;
geodesicFixedRadiusSearch (point_i, scale_values_[scale_i], nn_indices);
bool is_max_point = true, is_min_point = true;
for (std::vector<int>::iterator nn_it = nn_indices.begin (); nn_it != nn_indices.end (); ++nn_it)
if (F_scales_[scale_i][point_i] < F_scales_[scale_i][*nn_it])
is_max_point = false;
else
is_min_point = false;
is_min_scale[point_i] = is_min_point;
is_max_scale[point_i] = is_max_point;
}
is_min[scale_i] = is_min_scale;
is_max[scale_i] = is_max_scale;
}
// look for points that are min/max over three consecutive scales
for (size_t scale_i = 1; scale_i < scale_values_.size () - 1; ++scale_i)
{
for (size_t point_i = 0; point_i < input_->points.size (); ++point_i)
if ((is_min[scale_i - 1][point_i] && is_min[scale_i][point_i] && is_min[scale_i + 1][point_i]) ||
(is_max[scale_i - 1][point_i] && is_max[scale_i][point_i] && is_max[scale_i + 1][point_i]))
{
// add the point to the result vector
IndicesPtr region (new std::vector<int>);
region->push_back (static_cast<int> (point_i));
// and also add its scale-sized geodesic neighborhood
std::vector<int> nn_indices;
geodesicFixedRadiusSearch (point_i, scale_values_[scale_i], nn_indices);
region->insert (region->end (), nn_indices.begin (), nn_indices.end ());
rois.push_back (region);
}
}
}
void generateIndices(size_t step = 100)
{
indices->clear();
for(size_t i = 0; i < cloud->points.size(); i += step)
indices->push_back(i);
}
