pcl::people::HOG Class Reference

HOG represents a class for computing the HOG descriptor described in Dalal, N. More...

#include <pcl/people/hog.h>

Public Member Functions
	HOG ()
	Constructor.
virtual	~HOG ()
	Destructor.
void	gradMag (float *I, int h, int w, int d, float *M, float *O) const
	Compute gradient magnitude and orientation at each location (uses sse).
void	gradHist (float *M, float *O, int h, int w, int bin_size, int n_orients, bool soft_bin, float *H) const
	Compute n_orients gradient histograms per bin_size x bin_size block of pixels.
void	normalization (float *H, int h, int w, int bin_size, int n_orients, float clip, float *G) const
	Normalize histogram of gradients.
void	compute (float *I, int h, int w, int n_channels, int bin_size, int n_orients, bool soft_bin, float *descriptor)
	Compute HOG descriptor.
void	compute (float *I, float *descriptor) const
	Compute HOG descriptor with default parameters.

Protected Attributes
int	h_
	image height (default = 128)
int	w_
	image width (default = 64)
int	n_channels_
	image number of channels (default = 3)
int	bin_size_
	spatial bin size (default = 8)
int	n_orients_
	number of orientation bins (default = 9)
bool	soft_bin_
	if true, each pixel can contribute to multiple spatial bins (using bilinear interpolation) (default = true)
float	clip_
	value at which to clip histogram bins (default = 0.2)

Detailed Description

HOG represents a class for computing the HOG descriptor described in Dalal, N.

and Triggs, B., "Histograms of oriented gradients for human detection", CVPR 2005.

Author

Matteo Munaro, Stefano Ghidoni, Stefano Michieletto

Definition at line 54 of file hog.h.

Constructor & Destructor Documentation

HOG()

pcl::people::HOG::HOG

(

)

Constructor.

~HOG()

virtual pcl::people::HOG::~HOG ( )

virtual

Destructor.

Member Function Documentation

compute() [1/2]

void pcl::people::HOG::compute	(	float *	I,
		float *	descriptor ) const

Compute HOG descriptor with default parameters.

Parameters

[in]	I	Image as array of float between 0 and 1.
[out]	descriptor	HOG descriptor.

compute() [2/2]

void pcl::people::HOG::compute	(	float *	I,
		int	h,
		int	w,
		int	n_channels,
		int	bin_size,
		int	n_orients,
		bool	soft_bin,
		float *	descriptor )

Compute HOG descriptor.

Parameters

[in]	I	Image as array of float between 0 and 1.
[in]	h	Image height.
[in]	w	Image width.
[in]	n_channels	Image number of channels.
[in]	bin_size	Spatial bin size.
[in]	n_orients	Number of orientation bins.
[in]	soft_bin	If true, each pixel can contribute to multiple spatial bins (using bilinear interpolation).
[out]	descriptor	HOG descriptor.

Referenced by pcl::people::PersonClassifier< PointT >::evaluate().

gradHist()

void pcl::people::HOG::gradHist	(	float *	M,
		float *	O,
		int	h,
		int	w,
		int	bin_size,
		int	n_orients,
		bool	soft_bin,
		float *	H ) const

Compute n_orients gradient histograms per bin_size x bin_size block of pixels.

Parameters

[in]	M	Gradient magnitude for each image point.
[in]	O	Gradient orientation for each image point.
[in]	h	Image height.
[in]	w	Image width.
[in]	bin_size	Spatial bin size.
[in]	n_orients	Number of orientation bins.
[in]	soft_bin	If true, each pixel can contribute to multiple spatial bins (using bilinear interpolation).
[out]	H	Gradient histograms.

gradMag()

void pcl::people::HOG::gradMag	(	float *	I,
		int	h,
		int	w,
		int	d,
		float *	M,
		float *	O ) const

Compute gradient magnitude and orientation at each location (uses sse).

Parameters

[in]	I	Image as array of float.
[in]	h	Image height.
[in]	w	Image width.
[in]	d	Image number of channels.
[out]	M	Gradient magnitude for each image point.
[out]	O	Gradient orientation for each image point.

normalization()

void pcl::people::HOG::normalization	(	float *	H,
		int	h,
		int	w,
		int	bin_size,
		int	n_orients,
		float	clip,
		float *	G ) const

Normalize histogram of gradients.

Parameters

[in]	H	Gradient histograms.
[in]	h	Image height.
[in]	w	Image width.
[in]	bin_size	Spatial bin size.
[in]	n_orients	Number of orientation bins.
[in]	clip	Value at which to clip histogram bins.
[out]	G	Normalized gradient histograms.

Member Data Documentation

bin_size_

int pcl::people::HOG::bin_size_

protected

spatial bin size (default = 8)

Definition at line 174 of file hog.h.

clip_

float pcl::people::HOG::clip_

protected

value at which to clip histogram bins (default = 0.2)

Definition at line 183 of file hog.h.

h_

int pcl::people::HOG::h_

protected

image height (default = 128)

Definition at line 165 of file hog.h.

n_channels_

int pcl::people::HOG::n_channels_

protected

image number of channels (default = 3)

Definition at line 171 of file hog.h.

n_orients_

int pcl::people::HOG::n_orients_

protected

number of orientation bins (default = 9)

Definition at line 177 of file hog.h.

soft_bin_

bool pcl::people::HOG::soft_bin_

protected

if true, each pixel can contribute to multiple spatial bins (using bilinear interpolation) (default = true)

Definition at line 180 of file hog.h.

w_

int pcl::people::HOG::w_

protected

image width (default = 64)

Definition at line 168 of file hog.h.

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

• pcl/people/hog.h