sift.cl File Reference

Classes
struct	Feature
	Detected features. More...

Macros
#define	SIFT_IMG_BORDER   5
#define	SIFT_MAX_INTERP_STEPS   5
#define	SIFT_ORI_HIST_BINS   36
#define	SIFT_ORI_SIG_FCTR   1.5f
#define	SIFT_ORI_RADIUS   3.f * SIFT_ORI_SIG_FCTR
#define	SIFT_ORI_SMOOTH_PASSES   2
#define	SIFT_ORI_PEAK_RATIO   0.8f
#define	SIFT_DESCR_SCL_FCTR   3.f
#define	SIFT_DESCR_MAG_THR   0.2f
#define	SIFT_INT_DESCR_FCTR   512.f
#define	CV_PI   3.1415926535897932384626433832795f
#define	CV_2PI   6.283185307179586476925286766559f

Functions
void	ocl_ludcmp (float *varam_a, int *varam_indx)
void	ocl_lubksb (float *varam_a, const int *varam_indx, float *varam_b)
void	ocl_LUvar_solve (float *varam_a, float *varam_x, float *varam_b)
void	ocl_derivative (__global float *dog, int dog_width, int r, int c, float *dD)
void	ocl_hessian (__global float *prev_dog, __global float *dog, __global float *next_dog, int dog_width, int r, int c, float *H)
bool	__isExtremum (__global float *prev_dog, __global float *dog, __global float *next_dog, int dog_width, int r, int c)
bool	__interpExtremum (__global float *prev_dog, __global float *dog, __global float *next_dog, int dog_width, int dog_height, struct Feature *feat, int idx, int r, int c, int intervals, float contrast_thres, int curvature_thres)
__kernel void	scaleSpaceExtremaKernel (__global float *prev_dog, __global float *dog, __global float *next_dog, int dog_width, int dog_height, int idx, int intervals, float contrast_thres, int curvature_thres, __global struct Feature *feats, float prelim_contrast_thres, volatile __global int *atomic_cnt)
void	ocl_oriHist (__global float *gaussian, int width, int height, float *hist, int r, int c, int rad, float sigma)
__kernel void	calcFeatureOrisKernel (__global struct Feature *feats, __global float *gaussian_pyramid, __global int *gauss_size_accum, __global int *gauss_width, __global int *gauss_height, int layer_per_octave)
void	ocl_descriptorHist (__global float *gauss_data, int gauss_width, int gauss_height, float *hist, int r, int c, float ori, float scl, int d, int n)
void	ocl_normalizeDescriptor (float *descriptor, int cnt)
void	ocl_hist2Descriptor (float *hist, __global struct Feature *feat, int d, int n)
__kernel void	computeDescriptor (__global struct Feature *feats, __global float *gaussian_pyramid, __global int *gauss_size_accum, __global int *gauss_width, __global int *gauss_height, int layer_per_octave, int d, int n)

Macro Definition Documentation

CV_2PI

#define CV_2PI   6.283185307179586476925286766559f

CV_PI

#define CV_PI   3.1415926535897932384626433832795f

SIFT_DESCR_MAG_THR

#define SIFT_DESCR_MAG_THR   0.2f

SIFT_DESCR_SCL_FCTR

#define SIFT_DESCR_SCL_FCTR   3.f

SIFT_IMG_BORDER

#define SIFT_IMG_BORDER   5

SIFT_INT_DESCR_FCTR

#define SIFT_INT_DESCR_FCTR   512.f

SIFT_MAX_INTERP_STEPS

#define SIFT_MAX_INTERP_STEPS   5

SIFT_ORI_HIST_BINS

#define SIFT_ORI_HIST_BINS   36

SIFT_ORI_PEAK_RATIO

#define SIFT_ORI_PEAK_RATIO   0.8f

SIFT_ORI_RADIUS

#define SIFT_ORI_RADIUS   3.f * SIFT_ORI_SIG_FCTR

SIFT_ORI_SIG_FCTR

#define SIFT_ORI_SIG_FCTR   1.5f

SIFT_ORI_SMOOTH_PASSES

#define SIFT_ORI_SMOOTH_PASSES   2

Function Documentation

__interpExtremum()

bool __interpExtremum	(	__global float *	prev_dog,
		__global float *	dog,
		__global float *	next_dog,
		int	dog_width,
		int	dog_height,
		struct Feature *	feat,
		int	idx,
		int	r,
		int	c,
		int	intervals,
		float	contrast_thres,
		int	curvature_thres
	)

Interpolates a scale-space extremum's location

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
dog_height	height of current Dog image
feat	returned feature
idx	index of intervals
r	pixel's image row
c	pixel's image col
intervals	number of intervals per octave
contrast_thres	low threshold on feature contrast
curvature_thres	threshold on feature curvature

Returns

is a feature?

__isExtremum()

bool __isExtremum	(	__global float *	prev_dog,
		__global float *	dog,
		__global float *	next_dog,
		int	dog_width,
		int	r,
		int	c
	)

Determines whether a pixel is a scale-space extremum

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
r	pixel's image row
c	pixel's image col

Returns

is a extremum?

calcFeatureOrisKernel()

__kernel void calcFeatureOrisKernel	(	__global struct Feature *	feats,
		__global float *	gaussian_pyramid,
		__global int *	gauss_size_accum,
		__global int *	gauss_width,
		__global int *	gauss_height,
		int	layer_per_octave
	)

Computes a canonical orientation for each image feature

Parameters

feats	feature vector
gaussian_pyramid	gaussian pyramid
gauss_size_accum	gaussian accumulated total size OpenCL buffer
gauss_width	gaussian width OpenCL buffer
gauss_height	gaussian height OpenCL buffer
layer_per_octave	number of layers per octave

computeDescriptor()

__kernel void computeDescriptor	(	__global struct Feature *	feats,
		__global float *	gaussian_pyramid,
		__global int *	gauss_size_accum,
		__global int *	gauss_width,
		__global int *	gauss_height,
		int	layer_per_octave,
		int	d,
		int	n
	)

Computes feature descriptors (OpenCL)

Parameters

feats	feature vector
gaussian_pyramid	Gaussian pyramid
gauss_size_accum	gaussian accumulated total size OpenCL buffer
gauss_width	gaussian width OpenCL buffer
gauss_height	gaussian height OpenCL buffer
layer_per_octave	number of layers per octave in Gaussian pyramid
d	width of 2d hist
n	number of bins for descriptor

ocl_derivative()

void ocl_derivative	(	__global float *	dog,
		int	dog_width,
		int	r,
		int	c,
		float *	dD
	)

Calculate partial derivatives

Parameters

dog	Dog pyramid
dog_width	width of current Dog image
r	pixel's image row
c	pixel's image col
dD	array of partial derivatives

ocl_descriptorHist()

void ocl_descriptorHist	(	__global float *	gauss_data,
		int	gauss_width,
		int	gauss_height,
		float *	hist,
		int	r,
		int	c,
		float	ori,
		float	scl,
		int	d,
		int	n
	)

Computes the 2D array of orientation histograms

Parameters

gauss_data	gaussian image
gauss_width	the gaussian image width
gauss_height	the gaussian image height
hist	returned dxdxn hist vector
r	pixel's image row
c	pixel's image column
ori	orientation
scl	scl scale relative to image
d	width of 2d hist
n	number of bins for descriptor

ocl_hessian()

void ocl_hessian	(	__global float *	prev_dog,
		__global float *	dog,
		__global float *	next_dog,
		int	dog_width,
		int	r,
		int	c,
		float *	H
	)

Calculate 3D Hessian matrix

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
dog_height	height of current Dog image
r	pixel's image row
c	pixel's image col
H	array of Hessian matrix

ocl_hist2Descriptor()

void ocl_hist2Descriptor	(	float *	hist,
		__global struct Feature *	feat,
		int	d,
		int	n
	)

Converts 2d hist into 1d descriptor

Parameters

hist	2d histogram
feat	feature point
d	width of 2d hist
n	number of bins for descriptor

ocl_lubksb()

void ocl_lubksb	(	float *	varam_a,
		const int *	varam_indx,
		float *	varam_b
	)

Backsubstitution for LU

ocl_ludcmp()

void ocl_ludcmp	(	float *	varam_a,
		int *	varam_indx
	)

LU decomposition of a matrix

ocl_LUvar_solve()

void ocl_LUvar_solve	(	float *	varam_a,
		float *	varam_x,
		float *	varam_b
	)

Solve the least-squares solution using LU decomposition

ocl_normalizeDescriptor()

void ocl_normalizeDescriptor	(	float *	descriptor,
		int	cnt
	)

Normalize descriptor to length 1

Parameters

descriptor	descriptor vector
cnt	descriptor size

ocl_oriHist()

void ocl_oriHist	(	__global float *	gaussian,
		int	width,
		int	height,
		float *	hist,
		int	r,
		int	c,
		int	rad,
		float	sigma
	)

Compute gradient orientation histogram

Parameters

gaussian	gaussian image
width	the image width
height	the image height
hist	returned hist
r	pixel's image row
c	pixel's image column
rad	radius of selected region
sigma	sigma for gaussian smoothing

scaleSpaceExtremaKernel()

__kernel void scaleSpaceExtremaKernel	(	__global float *	prev_dog,
		__global float *	dog,
		__global float *	next_dog,
		int	dog_width,
		int	dog_height,
		int	idx,
		int	intervals,
		float	contrast_thres,
		int	curvature_thres,
		__global struct Feature *	feats,
		float	prelim_contrast_thres,
		volatile __global int *	atomic_cnt
	)

Detects features at extrema in DoG scale space

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
dog_height	height of current Dog image
idx	index of intervals
intervals	number of intervals per octave
contrast_thres	low threshold on feature contrast
curvature_thres	high threshold on feature ratio of principal curvatures
feats	returned feature vectors
prelim_contrast_thres	0.5f * (float)contrast_thres / intervals
atomic_cnt	returned keypoints