Covariant feature detectors - Definition. More...

#include "covdet.h"
#include <string.h>

Data Structures
struct	VlCovDet
	Covariant feature detector. More...

Functions
static int	_vl_resize_buffer (void *buffer, vl_size bufferSize, vl_size targetSize)
	Reallocate buffer.
static int	_vl_enlarge_buffer (void *buffer, vl_size bufferSize, vl_size targetSize)
	Enlarge buffer.
vl_size	vl_find_local_extrema_3 (vl_index *extrema, vl_size bufferSize, float const *map, vl_size width, vl_size height, vl_size depth, double threshold)
	Find extrema in 3D function.
vl_size	vl_find_local_extrema_2 (vl_index *extrema, vl_size bufferSize, float const *map, vl_size width, vl_size height, double threshold)
	Find extrema in 3D function.
vl_bool	vl_refine_local_extreum_3 (VlCovDetExtremum3 refined, float const map, vl_size width, vl_size height, vl_size depth, vl_index x, vl_index y, vl_index z)
	Refine extrema in 3D function.
vl_bool	vl_refine_local_extreum_2 (VlCovDetExtremum2 refined, float const map, vl_size width, vl_size height, vl_index x, vl_index y)
	Refine extrema in 3D function.
VlCovDet *	vl_covdet_new (VlCovDetMethod method)
	Create a new object instance.
void	vl_covdet_reset (VlCovDet *self)
	Reset object.
void	vl_covdet_delete (VlCovDet *self)
	Delete object instance.
int	vl_covdet_append_feature (VlCovDet self, VlCovDetFeature const feature)
	Append a feature to the internal buffer.
int	vl_covdet_put_image (VlCovDet self, float const image, vl_size width, vl_size height)
	Detect features in an image.
static void	_vl_det_hessian_response (float hessian, float const image, vl_size width, vl_size height, double step, double sigma)
	Scaled derminant of the Hessian filter.
static void	_vl_harris_response (float harris, float const image, vl_size width, vl_size height, double step, double sigma, double sigmaI, double alpha)
	Scale-normalised Harris response.
static void	_vl_dog_response (float dog, float const level1, float const *level2, vl_size width, vl_size height)
	Difference of Gaussian.
void	vl_covdet_detect (VlCovDet *self)
	Detect scale-space features.
vl_bool	vl_covdet_extract_patch_helper (VlCovDet self, double sigma1, double sigma2, float patch, vl_size resolution, double extent, double sigma, double(A_)[4], double(T_)[2], double d1, double d2)
	Helper for extracting patches.
vl_bool	vl_covdet_extract_patch_for_frame (VlCovDet self, float patch, vl_size resolution, double extent, double sigma, VlFrameOrientedEllipse frame)
	Helper for extracting patches.
int	vl_covdet_extract_affine_shape_for_frame (VlCovDet self, VlFrameOrientedEllipse adapted, VlFrameOrientedEllipse frame)
	Extract the affine shape for a feature frame.
void	vl_covdet_extract_affine_shape (VlCovDet *self)
	Extract the affine shape for the stored features.
VlCovDetFeatureOrientation *	vl_covdet_extract_orientations_for_frame (VlCovDet self, vl_size numOrientations, VlFrameOrientedEllipse frame)
	Extract the orientation(s) for a feature frame.
void	vl_covdet_extract_orientations (VlCovDet *self)
	Extract the orientation(s) for the stored features.
VlCovDetFeatureLaplacianScale *	vl_covdet_extract_laplacian_scales_for_frame (VlCovDet self, vl_size numScales, VlFrameOrientedEllipse frame)
	Extract the Laplacian scale(s) for a feature frame.
void	vl_covdet_extract_laplacian_scales (VlCovDet *self)
	Extract the Laplacian scales for the stored features.
void	vl_covdet_drop_features_outside (VlCovDet *self, double margin)
	Drop features (partially) outside the image.
vl_bool	vl_covdet_get_transposed (VlCovDet const *self)
	Get wether images are passed in transposed.
void	vl_covdet_set_transposed (VlCovDet *self, vl_bool t)
	Set the index of the first octave.
double	vl_covdet_get_edge_threshold (VlCovDet const *self)
	Get the edge threshold.
void	vl_covdet_set_edge_threshold (VlCovDet *self, double edgeThreshold)
	Set the edge threshold.
double	vl_covdet_get_peak_threshold (VlCovDet const *self)
	Get the peak threshold.
void	vl_covdet_set_peak_threshold (VlCovDet *self, double peakThreshold)
	Set the peak threshold.
vl_index	vl_covdet_get_first_octave (VlCovDet const *self)
	Get the index of the first octave.
void	vl_covdet_set_first_octave (VlCovDet *self, vl_index o)
	Set the index of the first octave.
vl_size	vl_covdet_get_octave_resolution (VlCovDet const *self)
	Get the octave resolution.
void	vl_covdet_set_octave_resolution (VlCovDet *self, vl_size r)
	Set the octave resolutuon.
vl_bool	vl_covdet_get_aa_accurate_smoothing (VlCovDet const *self)
	Get whether affine adaptation uses accurate smoothing.
void	vl_covdet_set_aa_accurate_smoothing (VlCovDet *self, vl_bool x)
	Set whether affine adaptation uses accurate smoothing.
double	vl_covdet_get_non_extrema_suppression_threshold (VlCovDet const *self)
	Get the non-extrema suppression threshold.
void	vl_covdet_set_non_extrema_suppression_threshold (VlCovDet *self, double x)
	Set the non-extrema suppression threshod.
vl_size	vl_covdet_get_num_non_extrema_suppressed (VlCovDet const *self)
	Get the number of non-extrema suppressed.
vl_size	vl_covdet_get_num_features (VlCovDet const *self)
	Get number of stored frames.
void *	vl_covdet_get_features (VlCovDet *self)
	Get the stored frames.
VlScaleSpace *	vl_covdet_get_gss (VlCovDet const *self)
	Get the Gaussian scale space.
VlScaleSpace *	vl_covdet_get_css (VlCovDet const *self)
	Get the cornerness measure scale space.
vl_size const *	vl_covdet_get_laplacian_scales_statistics (VlCovDet const self, vl_size numScales)
	Get the number of features found with a certain number of scales.

Detailed Description

Author:: Karel Lenc; Andrea Vedaldi; Michal Perdoch

Function Documentation

static void _vl_det_hessian_response	(	float *	hessian,
		float const *	image,
		vl_size	width,
		vl_size	height,
		double	step,
		double	sigma
	)

static

Parameters:

hessian	output image.
image	input image.
width	image width.
height	image height.
step	image sampling step (pixel size).
sigma	Gaussian smoothing of the input image.

static void _vl_dog_response	(	float *	dog,
		float const *	level1,
		float const *	level2,
		vl_size	width,
		vl_size	height
	)

static

Parameters:

dog	output image.
level1	input image at the smaller Gaussian scale.
level2	input image at the larger Gaussian scale.
width	image width.
height	image height.

static int _vl_enlarge_buffer	(	void **	buffer,
		vl_size *	bufferSize,
		vl_size	targetSize
	)

static

Parameters:

buffer
bufferSize
targetSize

Returns:: error code

static void _vl_harris_response	(	float *	harris,
		float const *	image,
		vl_size	width,
		vl_size	height,
		double	step,
		double	sigma,
		double	sigmaI,
		double	alpha
	)

static

Parameters:

harris	output image.
image	input image.
width	image width.
height	image height.
step	image sampling step (pixel size).
sigma	Gaussian smoothing of the input image.
sigmaI	integration scale.
alpha	factor in the definition of the Harris score.

static int _vl_resize_buffer	(	void **	buffer,
		vl_size *	bufferSize,
		vl_size	targetSize
	)

static

Parameters:

buffer
bufferSize
targetSize

Returns:: error code

int vl_covdet_append_feature	(	VlCovDet *	self,
		VlCovDetFeature const *	feature
	)

Parameters:

self	object.
feature	a pointer to the feature to append.

Returns:: status.

The feature is copied. The function may fail with status equal to VL_ERR_ALLOC if there is insufficient memory.

void vl_covdet_delete ( VlCovDet * self )

Parameters:

self object.

void vl_covdet_detect ( VlCovDet * self )

Parameters:

method

Returns:: new covariant detector.

void vl_covdet_drop_features_outside	(	VlCovDet *	self,
		double	margin
	)

Parameters:

self	object.
margin	geometric marging.

The feature extent is defined by maring. A bounding box in the normalised feature frame containin a circle of radius maring is created and mapped to the image by the feature frame transformation. Then the feature is dropped if the bounding box is not contained in the image.

For example, setting margin to zero drops a feature only if its center is not contained.

Typically a valua of margin equal to 1 or 2 is used.

void vl_covdet_extract_affine_shape ( VlCovDet * self )

Parameters:

self object.

This function may discard features for which no affine shape can reliably be detected.

int vl_covdet_extract_affine_shape_for_frame	(	VlCovDet *	self,
		VlFrameOrientedEllipse *	adapted,
		VlFrameOrientedEllipse	frame
	)

Parameters:

self	object.
adapted	the shape-adapted frame.
frame	the input frame.

Returns:: VL_ERR_OK if affine adaptation is successful.

This function may fail if adaptation is unsuccessful or if memory is insufficient.

void vl_covdet_extract_laplacian_scales ( VlCovDet * self )

Parameters:

self object.

Note that, since more than one orientation can be detected for each feature, this function may create copies of them, one for each orientation.

VlCovDetFeatureLaplacianScale* vl_covdet_extract_laplacian_scales_for_frame	(	VlCovDet *	self,
		vl_size *	numScales,
		VlFrameOrientedEllipse	frame
	)

Parameters:

self	object.
numScales	the number of detected scales.

Returns:: an array of detected scales.

The function returns NULL if memory is insufficient.

void vl_covdet_extract_orientations ( VlCovDet * self )

Parameters:

self object.

Note that, since more than one orientation can be detected for each feature, this function may create copies of them, one for each orientation.

VlCovDetFeatureOrientation* vl_covdet_extract_orientations_for_frame	(	VlCovDet *	self,
		vl_size *	numOrientations,
		VlFrameOrientedEllipse	frame
	)

Parameters:

self	object.
numOrientations	the number of detected orientations.

Returns:: an array of detected orientations with their scores.

The returned array is a matrix of size \( 2 \times n \) where n is the number of detected orientations.

The function returns NULL if memory is insufficient.

vl_bool vl_covdet_extract_patch_for_frame	(	VlCovDet *	self,
		float *	patch,
		vl_size	resolution,
		double	extent,
		double	sigma,
		VlFrameOrientedEllipse	frame
	)

Parameters:

self	object.
patch	buffer.
resolution	patch resolution.
extent	patch extent.
sigma	desired smoothing in the patch frame.
frame	feature frame.

The function considers a patch of extent [-extent,extent] on each side, with a side counting 2*resolution+1 pixels. In attempts to extract from the scale space a patch baed on the affine warping specified by frame in such a way that the resulting smoothing of the image is sigma (in the patch frame).

The transformation is specified by the matrices A and T embedded in the feature frame. Note that this transformation maps pixels from the patch frame to the image frame.

vl_bool vl_covdet_extract_patch_helper	(	VlCovDet *	self,
		double *	sigma1,
		double *	sigma2,
		float *	patch,
		vl_size	resolution,
		double	extent,
		double	sigma,
		double(A_)	[4],
		double(T_)	[2],
		double	d1,
		double	d2
	)

Parameters:

self	object.
sigma1	actual patch smoothing along the first axis (out).
sigma2	actual patch smoothing along the second axis (out).
patch	buffer.
resolution	patch resolution.
extent	patch extent.
sigma	desired smoothing in the patch frame.
A	linear transfomration from patch to image.
T	translation from patch to image.
d1	first singular value A.
d2	second singular value of A.

vl_bool vl_covdet_get_aa_accurate_smoothing ( VlCovDet const * self )

Parameters:

self object.

Returns:: true if accurate smoothing is used.

VlScaleSpace* vl_covdet_get_css ( VlCovDet const * self )

Returns:: cornerness measure scale space.

A cornerness measure scale space exists only after calling vl_covdet_detect. Otherwise the function returns NULL.

double vl_covdet_get_edge_threshold ( VlCovDet const * self )

Parameters:

self	::VlCovDet object.

Returns:: the edge threshold.

void* vl_covdet_get_features ( VlCovDet * self )

Returns:: frames stored in the detector.

vl_index vl_covdet_get_first_octave ( VlCovDet const * self )

Parameters:

self	::VlCovDet object.

Returns:: index of the first octave.

VlScaleSpace* vl_covdet_get_gss ( VlCovDet const * self )

Returns:: Gaussian scale space.

A Gaussian scale space exists only after calling vl_covdet_put_image. Otherwise the function returns NULL.

vl_size const* vl_covdet_get_laplacian_scales_statistics	(	VlCovDet const *	self,
		vl_size *	numScales
	)

Parameters:

sellf	object.
numScales	length of the histogram (out).

Returns:: histogram.

Calling this function makes sense only after running a detector that uses the Laplacian as a secondary measure for scale detection

double vl_covdet_get_non_extrema_suppression_threshold ( VlCovDet const * self )

Parameters:

self object.

Returns:: threshold.

vl_size vl_covdet_get_num_features ( VlCovDet const * self )

Returns:: number of frames stored in the detector.

vl_size vl_covdet_get_num_non_extrema_suppressed ( VlCovDet const * self )

Parameters:

self object.

Returns:: number.

vl_size vl_covdet_get_octave_resolution ( VlCovDet const * self )

Parameters:

self	::VlCovDet object.

Returns:: octave resolution.

double vl_covdet_get_peak_threshold ( VlCovDet const * self )

Parameters:

self	::VlCovDet object.

Returns:: the peak threshold.

vl_bool vl_covdet_get_transposed ( VlCovDet const * self )

Parameters:

self	::VlCovDet object.

Returns:: whether images are transposed.

VlCovDet* vl_covdet_new ( VlCovDetMethod method )

Parameters:

method method for covariant feature detection.

Returns:: new covariant detector.

int vl_covdet_put_image	(	VlCovDet *	self,
		float const *	image,
		vl_size	width,
		vl_size	height
	)

Parameters:

self	object.
image	image to process.
width	image width.
height	image height.

Returns:: status.

width and height must be at least one pixel. The function fails by returing VL_ERR_ALLOC if the memory is insufficient.

void vl_covdet_reset ( VlCovDet * self )

Parameters:

self object.

This function removes any buffered features and frees other internal buffers.

void vl_covdet_set_aa_accurate_smoothing	(	VlCovDet *	self,
		vl_bool	x
	)

Parameters:

self	object.
x	whether accurate smoothing should be usd.

void vl_covdet_set_edge_threshold	(	VlCovDet *	self,
		double	edgeThreshold
	)

Parameters:

self	::VlCovDet object.
the	edge threshold.

The edge threshold must be non-negative.

void vl_covdet_set_first_octave	(	VlCovDet *	self,
		vl_index	o
	)

Parameters:

self	::VlCovDet object.
index	of the first octave.

Calling this function resets the detector.

void vl_covdet_set_non_extrema_suppression_threshold	(	VlCovDet *	self,
		double	x
	)

Parameters:

self	object.
x	threshold.

void vl_covdet_set_octave_resolution	(	VlCovDet *	self,
		vl_size	r
	)

Parameters:

self	::VlCovDet object.
octave	resoltuion.

Calling this function resets the detector.

void vl_covdet_set_peak_threshold	(	VlCovDet *	self,
		double	peakThreshold
	)

Parameters:

self	::VlCovDet object.
the	peak threshold.

The peak threshold must be non-negative.

void vl_covdet_set_transposed	(	VlCovDet *	self,
		vl_bool	t
	)

Parameters:

self	::VlCovDet object.
t	whether images are transposed.

vl_size vl_find_local_extrema_2	(	vl_index **	extrema,
		vl_size *	bufferSize,
		float const *	map,
		vl_size	width,
		vl_size	height,
		double	threshold
	)

Parameters:

extrema
bufferSize
map	a 3D array representing the map.
width	of the map.
height	of the map.
deepth	of the map.
threshold	minumum extremum value.

Returns:: number of extrema found.

vl_size vl_find_local_extrema_3	(	vl_index **	extrema,
		vl_size *	bufferSize,
		float const *	map,
		vl_size	width,
		vl_size	height,
		vl_size	depth,
		double	threshold
	)

Parameters:

extrema
bufferSize
map	a 3D array representing the map.
width	of the map.
height	of the map.
deepth	of the map.
threshold	minumum extremum value.

Returns:: number of extrema found.

vl_bool vl_refine_local_extreum_2	(	VlCovDetExtremum2 *	refined,
		float const *	map,
		vl_size	width,
		vl_size	height,
		vl_index	x,
		vl_index	y
	)

Parameters:

refined	refined extrema.
map	a 3D array representing the map.
width	of the map.
height	of the map.
deepth	of the map.
x
y
z

Returns:: extrema refinement was stable.

vl_bool vl_refine_local_extreum_3	(	VlCovDetExtremum3 *	refined,
		float const *	map,
		vl_size	width,
		vl_size	height,
		vl_size	depth,
		vl_index	x,
		vl_index	y,
		vl_index	z
	)

Parameters:

refined	refined extrema.
map	a 3D array representing the map.
width	of the map.
height	of the map.
deepth	of the map.
x
y
z

Returns:: extrema refinement was stable.

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Data Structures

Functions

Detailed Description

Function Documentation