/home/laradmin/lar/perception/planarobstacles/lidar_segmentation/src/clustering.h File Reference

Clustering related functions header. More...

#include <vector>
#include "geometry_msgs/Point.h"
#include "sensor_msgs/LaserScan.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.
PointPtr	calculateClusterCentroid (vector< PointPtr > support_points)
	Calculates the cluster's centroid.
PointPtr	calculateClusterMedian (vector< PointPtr > support_points)
	Calculates the cluster's central point.
double	cosineDistance (vector< double > &vect1, vector< double > &vect2)
	Calculates the cosine distance between 2 vectors.
double	deg2rad (double angle)
	Converts degree values to radian values.
int	dietmayerClustering (vector< PointPtr > &points, double C0, vector< ClusterPtr > &clusters_Dietmayer)
	Performs Segmentation operation with the Dietmayer Segmentation Algorithm.
int	nnClustering (vector< PointPtr > &points, double threshold, vector< ClusterPtr > &clusters_nn)
	Performs Segmentation operation with the Spacial Nerarest Neighbor Algorithm.
int	premebidaClustering (vector< PointPtr > &points, double threshold_prem, vector< ClusterPtr > &clusters_Premebida)
	Performs Segmentation operation with the Multivariable Segmentation Algorithm.
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.
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.
int	simpleClustering (vector< PointPtr > &points, double threshold, vector< ClusterPtr > &clusters)
	Performs a Simple Segmentation operation.

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.

/home/laradmin/lar/perception/planarobstacles/lidar_segmentation/src/clustering.h File Reference

Classes

Typedefs

Functions

Detailed Description

Typedef Documentation

Function Documentation