dd/d8d/dbscan_8hpp_source.html

#include <string>

#include <vector>


#include "clustering/clustering.hpp"


class DBSCAN : public Clustering {

public:

  DBSCAN(int min_cluster_size, double neighbours_dist_threshold);


  void clustering(const sensor_msgs::msg::PointCloud2::SharedPtr& point_cloud,

                  std::vector<Cluster>* clusters) const override;


private:

  int min_cluster_size;

  double neighbours_dist_threshold;

};


Clustering
Abstract base class for clustering point clouds.
Definition clustering.hpp:14

DBSCAN
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm implementat...
Definition dbscan.hpp:14

DBSCAN::min_cluster_size
int min_cluster_size
Minimum number of points required to form a cluster.
Definition dbscan.hpp:37

DBSCAN::clustering
void clustering(const sensor_msgs::msg::PointCloud2::SharedPtr &point_cloud, std::vector< Cluster > *clusters) const override
Clusters the input point cloud into groups using the DBSCAN algorithm.
Definition dbscan.cpp:6

DBSCAN::neighbours_dist_threshold
double neighbours_dist_threshold
Maximum distance between points to be considered as neighbors.
Definition dbscan.hpp:38

clustering.hpp