GentleBoostCascadedClassifier2 Class Reference [Machine Perception Primitives]

Machine Perception Primitive: An implementation of a GentleBoost cascaded classifier for full image object search. More...

#include <GentleBoostCascadedClassifier2.h>

Inheritance diagram for GentleBoostCascadedClassifier2:

Collaboration diagram for GentleBoostCascadedClassifier2:

List of all members.

Public Member Functions
	GentleBoostCascadedClassifier2 ()
	Constructor.
	GentleBoostCascadedClassifier2 (const GentleBoostCascadedClassifier2 &copy)
	Copy Constructor.
GentleBoostCascadedClassifier2 &	operator= (const GentleBoostCascadedClassifier2 &rhs)
	Assignment operator.
	~GentleBoostCascadedClassifier2 ()
	Destructor.
void	setTrainingParams (double maxPosRejects=0.001)
	Set parameters used to determine the rejection threshold for each cascade step.
virtual PerformanceMetrics	trainOneRound (int patience=1, int boostRounds=1)
	Train boosted classifier for one round by searching for one good feature, and adding it.
void	setHardNegativeTrainingExamplesFromBGImages ()
	Replace the rejected negative example patches in the current training set with patches in taken from background images that haven't yet been rejected. The background image pool is specified with setBGTrainingImagesFromImageDataset().
bool	exhaustedAllNegPatches ()
	Returns "yes" if all known negative patches have been rejected. This is a good time to stop training.
Static Public Member Functions
static double	featureCost (const PerformanceMetrics &a)

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Detailed Description

Machine Perception Primitive: An implementation of a GentleBoost cascaded classifier for full image object search.

The GentleBoost approach is described in Fasel's "Learning Real-Time Object Detectors: Probabilistic Generative Approaches", 2006 (see Related Publications).

GentleBoostCascadedClassifier is designed for full frame object detection.

Author:

Nicholas Butko

Date:

2010 version 0.4

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Member Function Documentation

double GentleBoostCascadedClassifier2::featureCost

(

const PerformanceMetrics &

a )

[static]

Write to file. Read from file.

Reimplemented from GentleBoostClassifier2.

void GentleBoostCascadedClassifier2::setTrainingParams

(

double

maxPosRejects = 0.001 )

Set parameters used to determine the rejection threshold for each cascade step.

The threshold is chosen as soon as more than a fraction maxPosRejects of the remaining positive patches have been rejected, or when a fraction desiredNegRejects of the remaining negative patches have been rejected.

Parameters:

maxPosRejects	Max fraction of remaining positive patches rejected per training round.
desiredNegRejects	Desired fraction of remaining negative patches rejected per training round.

PerformanceMetrics GentleBoostCascadedClassifier2::trainOneRound	(	int	patience = 1,
		int	boostRounds = 1
	)		[virtual]

Train boosted classifier for one round by searching for one good feature, and adding it.

Parameters:

patience	How long do you want to wait to find a good feature?
boostRounds	Train for multiple rounds of boosting on one feature: makes the classifier more discriminative but more prone to overfit.

Reimplemented from GentleBoostClassifier2.

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The documentation for this class was generated from the following files:

• /Users/nick/projects/NickThesis/Code/OpenCV/src/GentleBoostCascadedClassifier2.h
• /Users/nick/projects/NickThesis/Code/OpenCV/src/GentleBoostCascadedClassifier2.cpp