Module pointcloud.importer

Package de.grogra.pointcloud.clustering

Class DBSCAN

java.lang.Object

de.grogra.pointcloud.clustering.DBSCAN

public abstract class DBSCAN
extends Object

Constructor Summary

Constructors

Constructor	Description
DBSCAN()

Method Summary

Modifier and Type	Method	Description
static List<PointCloudBaseImpl>	cluster(PointCloudBaseImpl pc, double epsilon, int minimumNeighbours, int octreeDepth, boolean removeNoiseCluster)	Clusters the given point cloud with the DBSCAN algorithm by the given parameters
static List<ClusterPoint>	getLeavesAsPointArray(PointCloudBase pc)	Converts the leaf nodes of the point cloud to ClusterPoints

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

DBSCAN

public DBSCAN()

Method Details

cluster

public static List<PointCloudBaseImpl> cluster(PointCloudBaseImpl pc,
 double epsilon,
 int minimumNeighbours,
 int octreeDepth,
 boolean removeNoiseCluster)

Clusters the given point cloud with the DBSCAN algorithm by the given parameters

Parameters:

pc - point cloud to be clustered

epsilon - The maximum distance for two points that are in the same cluster

minimumNeighbours - The minimum number of neighbors that must exist for a point to be no noise-cluster point.

octreeDepth - The number of layers in the octree that is used to cluster the point cloud. This must be > 1 to decrease the runtime of the clustering algorithm.

removeNoiseCluster - The indicator that can be set to true to remove all points that are not explicitly in an other point cloud.

Returns:

A list of point clouds representing the cluster

getLeavesAsPointArray

public static List<ClusterPoint> getLeavesAsPointArray(PointCloudBase pc)

Converts the leaf nodes of the point cloud to ClusterPoints

Returns:

a list containing the leaves as ClusterPoints