Clustering related functions header. More...

#include <vector>
#include "geometry_msgs/Point.h"
#include "sensor_msgs/LaserScan.h"

Include dependency graph for clustering.h:

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Classes
class	Cluster

Typedefs
typedef boost::shared_ptr < Cluster >	ClusterPtr

typedef boost::shared_ptr< Point >	PointPtr

Functions
int	abdClustering (vector< PointPtr > &points, double lambda, vector< ClusterPtr > &clusters_ABD)
	Performs Segmentation operation with the Adaptative Breakpoint Detector. More...

PointPtr	calculateClusterCentroid (vector< PointPtr > support_points)
	Calculates the cluster's centroid. More...

PointPtr	calculateClusterMedian (vector< PointPtr > support_points)
	Calculates the cluster's central point. More...

double	cosineDistance (vector< double > &vect1, vector< double > &vect2)
	Calculates the cosine distance between 2 vectors. More...

double	deg2rad (double angle)
	Converts degree values to radian values. More...

int	dietmayerClustering (vector< PointPtr > &points, double C0, vector< ClusterPtr > &clusters_Dietmayer)
	Performs Segmentation operation with the Dietmayer Segmentation Algorithm. More...

int	nnClustering (vector< PointPtr > &points, double threshold, vector< ClusterPtr > &clusters_nn)
	Performs Segmentation operation with the Spacial Nerarest Neighbor Algorithm. More...

int	premebidaClustering (vector< PointPtr > &points, double threshold_prem, vector< ClusterPtr > &clusters_Premebida)
	Performs Segmentation operation with the Multivariable Segmentation Algorithm. More...

vector< double >	rangeFeatures (double range1, double range2, PointPtr range1cart, PointPtr range2cart)
	A auxiliary function of the premebidaClustering function Calculates the a set of atributes of a pair of laser points. More...

int	santosClustering (vector< PointPtr > &points, double C0, double beta, vector< ClusterPtr > &clusters_Santos)
	Performs Segmentation operation with the Santos Approach from the Dietmayer Segmentation Algorithm. More...

int	simpleClustering (vector< PointPtr > &points, double threshold, vector< ClusterPtr > &clusters)
	Performs a Simple Segmentation operation. More...

Detailed Description

Clustering related functions header.

Author: Daniel Coimbra

Definition in file clustering.h.

Typedef Documentation

typedef boost::shared_ptr<Cluster> ClusterPtr

Definition at line 70 of file clustering.h.

typedef boost::shared_ptr<Point> PointPtr

Definition at line 42 of file clustering.h.

Function Documentation

int abdClustering	(	vector< PointPtr > &	points,
		double	lambda,
		vector< ClusterPtr > &	clusters_ABD
	)

Performs Segmentation operation with the Adaptative Breakpoint Detector.

Parameters

points	incoming Laser Points
lamda	auxiliary parameter
clusters_ABD	clusters output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the Adaptative Breakpoint Detector

Definition at line 384 of file clustering.cpp.

PointPtr calculateClusterCentroid ( vector< PointPtr > support_points )

Calculates the cluster's centroid.

Parameters

support_points cluster's support points

Returns: The coordinates of the cluster's centroid

Definition at line 702 of file clustering.cpp.

PointPtr calculateClusterMedian ( vector< PointPtr > support_points )

Calculates the cluster's central point.

Parameters

support_points cluster's support points

Returns: The coordinates of the cluster's central point

Definition at line 747 of file clustering.cpp.

double cosineDistance	(	vector< double > &	vect1,
		vector< double > &	vect2
	)

Calculates the cosine distance between 2 vectors.

Parameters

vect1	input vector with the range atributes from the fist pair
vect2	input vector with the range atributes from the second pair

Returns: Cosine distance

Definition at line 665 of file clustering.cpp.

double deg2rad ( double angle )

Converts degree values to radian values.

Parameters

angle angle value in degrees

Returns: angle value in radians

Definition at line 687 of file clustering.cpp.

int dietmayerClustering	(	vector< PointPtr > &	points,
		double	C0,
		vector< ClusterPtr > &	clusters_Dietmayer
	)

Performs Segmentation operation with the Dietmayer Segmentation Algorithm.

Parameters

points	incoming Laser Points
C0	parameter used for noise reduction
clusters_Dietmayer	output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the Dietmayer Segmentation Algorithm

Definition at line 144 of file clustering.cpp.

int nnClustering	(	vector< PointPtr > &	points,
		double	threshold,
		vector< ClusterPtr > &	clusters_nn
	)

Performs Segmentation operation with the Spacial Nerarest Neighbor Algorithm.

Parameters

points	incoming Laser Points
threshold	distance value used to break clusters
clusters_nn	clusters output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the Spacial Nerarest Neighbor Algorithm

Definition at line 468 of file clustering.cpp.

int premebidaClustering	(	vector< PointPtr > &	points,
		double	threshold_prem,
		vector< ClusterPtr > &	clusters_Premebida
	)

Performs Segmentation operation with the Multivariable Segmentation Algorithm.

Parameters

points	incoming Laser Points
threshold_prem	cosine distance value used to break clusters
clusters_Premebida	clusters output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the Multivariable Segmentation Algorithm

Definition at line 239 of file clustering.cpp.

vector<double> rangeFeatures	(	double	range1,
		double	range2,
		PointPtr	range1cart,
		PointPtr	range2cart
	)

A auxiliary function of the premebidaClustering function Calculates the a set of atributes of a pair of laser points.

Parameters

range1	range value of the the first point
range2	range value of the the second point
range1cart	cartesian value of the first point
range2cart	cartesian value of the second point

Returns: Vector of atributes

Definition at line 635 of file clustering.cpp.

int santosClustering	(	vector< PointPtr > &	points,
		double	C0,
		double	beta,
		vector< ClusterPtr > &	clusters_Santos
	)

Performs Segmentation operation with the Santos Approach from the Dietmayer Segmentation Algorithm.

Parameters

points	incoming Laser Points
C0	parameter used for noise reduction
beta	parameter aiming to reduce the dependence of the segmentation with respect to the distance between the LRF and the objects
clusters_Santos	clusters output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the Santos Approach from the Dietmayer Segmentation Algorithm

Definition at line 538 of file clustering.cpp.

int simpleClustering	(	vector< PointPtr > &	points,
		double	threshold,
		vector< ClusterPtr > &	clusters
	)

Performs a Simple Segmentation operation.

Parameters

points	incoming Laser Points
threshold	distance value used to break clusters
clusters	output vector of clusters, these clusters use the Cluster class

Returns: Number of clusters resulted from the simple segmentation algorithm

Definition at line 49 of file clustering.cpp.

Classes

Typedefs

Functions

Detailed Description

Typedef Documentation

Function Documentation