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Remove GSURF descriptor from KAZE algorithm

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This commit is contained in:
Ievgen Khvedchenia
2014-05-10 20:57:37 +03:00
parent a068ccbf51
commit 029a8c443a
7 changed files with 25 additions and 718 deletions
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19
modules/features2d/doc/feature_detection_and_description.rst
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@@ -256,29 +256,12 @@ KAZE
Class implementing the KAZE keypoint detector and descriptor extractor, described in [ABD12]_. ::
class CV_EXPORTS_W KAZE : public Feature2D
{
public:
/// KAZE Descriptor Type
enum DESCRIPTOR_TYPE {
DESCRIPTOR_MSURF = 1,
DESCRIPTOR_GSURF = 2
};
CV_WRAP KAZE();
explicit KAZE(DESCRIPTOR_TYPE descriptor_type, bool extended, bool upright);
....
};
KAZE::KAZE
----------
The KAZE constructor
.. ocv:function:: KAZE::KAZE(DESCRIPTOR_TYPE descriptor_type, bool extended, bool upright)
.. ocv:function:: KAZE::KAZE(bool extended, bool upright)
:param descriptor_type: Type of the extracted descriptor.
:param extended: Set to enable extraction of extended (128-byte) descriptor.
:param upright: Set to enable use of upright descriptors (non rotation-invariant).

8
modules/features2d/include/opencv2/features2d.hpp
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@@ -893,14 +893,8 @@ KAZE implementation
class CV_EXPORTS_W KAZE : public Feature2D
{
public:
/// AKAZE Descriptor Type
enum DESCRIPTOR_TYPE {
DESCRIPTOR_MSURF = 1,
DESCRIPTOR_GSURF = 2
};
CV_WRAP KAZE();
explicit KAZE(DESCRIPTOR_TYPE descriptor_type, bool extended, bool upright);
CV_WRAP explicit KAZE(bool extended, bool upright);
virtual ~KAZE();

1
modules/features2d/src/features2d_init.cpp
View File

@@ -126,7 +126,6 @@ CV_INIT_ALGORITHM(GFTTDetector, "Feature2D.GFTT",
///////////////////////////////////////////////////////////////////////////////////////////////////////////
CV_INIT_ALGORITHM(KAZE, "Feature2D.KAZE",
obj.info()->addParam(obj, "descriptor", obj.descriptor);
obj.info()->addParam(obj, "upright", obj.upright);
obj.info()->addParam(obj, "extended", obj.extended))

11
modules/features2d/src/kaze.cpp
View File

@@ -53,15 +53,13 @@ http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla12eccv.pd
namespace cv
{
KAZE::KAZE()
: descriptor(DESCRIPTOR_MSURF)
, extended(false)
: extended(false)
, upright(false)
{
}
KAZE::KAZE(DESCRIPTOR_TYPE _descriptor_type, bool _extended, bool _upright)
: descriptor(_descriptor_type)
, extended(_extended)
KAZE::KAZE(bool _extended, bool _upright)
: extended(_extended)
, upright(_upright)
{
@@ -111,7 +109,6 @@ namespace cv
KAZEOptions options;
options.img_width = img.cols;
options.img_height = img.rows;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.extended = extended;
options.upright = upright;
@@ -146,7 +143,6 @@ namespace cv
KAZEOptions options;
options.img_width = img.cols;
options.img_height = img.rows;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.extended = extended;
options.upright = upright;
@@ -174,7 +170,6 @@ namespace cv
KAZEOptions options;
options.img_width = img.cols;
options.img_height = img.rows;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.extended = extended;
options.upright = upright;

4
modules/features2d/src/kaze/KAZEConfig.h
View File

@@ -22,8 +22,7 @@ struct KAZEOptions {
};
KAZEOptions()
: descriptor(cv::KAZE::DESCRIPTOR_MSURF)
, diffusivity(PM_G2)
: diffusivity(PM_G2)
, soffset(1.60f)
, omax(4)
@@ -46,7 +45,6 @@ struct KAZEOptions {
{
}
cv::KAZE::DESCRIPTOR_TYPE descriptor;
DIFFUSIVITY_TYPE diffusivity;
float soffset;

693
modules/features2d/src/kaze/KAZEFeatures.cpp
View File

@@ -500,10 +500,10 @@ void KAZEFeatures::Do_Subpixel_Refinement(std::vector<cv::KeyPoint> &kpts) {
//*************************************************************************************
//*************************************************************************************
class MSURF_Descriptor_Invoker : public cv::ParallelLoopBody
class KAZE_Descriptor_Invoker : public cv::ParallelLoopBody
{
public:
MSURF_Descriptor_Invoker(std::vector<cv::KeyPoint> &kpts, cv::Mat &desc, std::vector<TEvolution>& evolution, const KAZEOptions& _options)
KAZE_Descriptor_Invoker(std::vector<cv::KeyPoint> &kpts, cv::Mat &desc, std::vector<TEvolution>& evolution, const KAZEOptions& _options)
: _kpts(&kpts)
, _desc(&desc)
, _evolution(&evolution)
@@ -511,7 +511,7 @@ public:
{
}
virtual ~MSURF_Descriptor_Invoker()
virtual ~KAZE_Descriptor_Invoker()
{
}
@@ -528,82 +528,26 @@ public:
{
kpts[i].angle = 0.0;
if (options.extended)
Get_MSURF_Upright_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
Get_KAZE_Upright_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
else
Get_MSURF_Upright_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
Get_KAZE_Upright_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
}
else
{
KAZEFeatures::Compute_Main_Orientation(kpts[i], evolution, options);
if (options.extended)
Get_MSURF_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
Get_KAZE_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
else
Get_MSURF_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
Get_KAZE_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
}
}
}
private:
void Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc) const;
void Get_MSURF_Descriptor_64(const cv::KeyPoint& kpt, float* desc) const;
void Get_MSURF_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc) const;
void Get_MSURF_Descriptor_128(const cv::KeyPoint& kpt, float *desc) const;
std::vector<cv::KeyPoint> * _kpts;
cv::Mat * _desc;
std::vector<TEvolution> * _evolution;
KAZEOptions options;
};
class GSURF_Descriptor_Invoker : public cv::ParallelLoopBody
{
public:
GSURF_Descriptor_Invoker(std::vector<cv::KeyPoint> &kpts, cv::Mat &desc, std::vector<TEvolution>& evolution, const KAZEOptions& _options)
: _kpts(&kpts)
, _desc(&desc)
, _evolution(&evolution)
, options(_options)
{
}
virtual ~GSURF_Descriptor_Invoker()
{
}
void operator() (const cv::Range& range) const
{
std::vector<cv::KeyPoint> &kpts = *_kpts;
cv::Mat &desc = *_desc;
std::vector<TEvolution> &evolution = *_evolution;
for (int i = range.start; i < range.end; i++)
{
kpts[i].angle = 0.0;
if (options.upright)
{
kpts[i].angle = 0.0;
if (options.extended)
Get_GSURF_Upright_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
else
Get_GSURF_Upright_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
}
else
{
KAZEFeatures::Compute_Main_Orientation(kpts[i], evolution, options);
if (options.extended)
Get_GSURF_Descriptor_128(kpts[i], desc.ptr<float>((int)i));
else
Get_GSURF_Descriptor_64(kpts[i], desc.ptr<float>((int)i));
}
}
}
private:
void Get_GSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc) const;
void Get_GSURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) const;
void Get_GSURF_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc) const;
void Get_GSURF_Descriptor_128(const cv::KeyPoint& kpt, float* desc) const;
void Get_KAZE_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc) const;
void Get_KAZE_Descriptor_64(const cv::KeyPoint& kpt, float* desc) const;
void Get_KAZE_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc) const;
void Get_KAZE_Descriptor_128(const cv::KeyPoint& kpt, float *desc) const;
std::vector<cv::KeyPoint> * _kpts;
cv::Mat * _desc;
@@ -626,16 +570,7 @@ void KAZEFeatures::Feature_Description(std::vector<cv::KeyPoint> &kpts, cv::Mat
desc = Mat::zeros((int)kpts.size(), 64, CV_32FC1);
}
switch (options.descriptor)
{
case cv::KAZE::DESCRIPTOR_MSURF:
cv::parallel_for_(cv::Range(0, (int)kpts.size()), MSURF_Descriptor_Invoker(kpts, desc, evolution_, options));
break;
case cv::KAZE::DESCRIPTOR_GSURF:
cv::parallel_for_(cv::Range(0, (int)kpts.size()), GSURF_Descriptor_Invoker(kpts, desc, evolution_, options));
break;
};
cv::parallel_for_(cv::Range(0, (int)kpts.size()), KAZE_Descriptor_Invoker(kpts, desc, evolution_, options));
}
//*************************************************************************************
@@ -728,7 +663,7 @@ void KAZEFeatures::Compute_Main_Orientation(cv::KeyPoint &kpt, const std::vector
* from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
* ECCV 2008
*/
void MSURF_Descriptor_Invoker::Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
void KAZE_Descriptor_Invoker::Get_KAZE_Upright_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
{
float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0, gauss_s1 = 0.0, gauss_s2 = 0.0;
float rx = 0.0, ry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -862,7 +797,7 @@ void MSURF_Descriptor_Invoker::Get_MSURF_Upright_Descriptor_64(const cv::KeyPoin
* from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
* ECCV 2008
*/
void MSURF_Descriptor_Invoker::Get_MSURF_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
void KAZE_Descriptor_Invoker::Get_KAZE_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
{
float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0, gauss_s1 = 0.0, gauss_s2 = 0.0;
float rx = 0.0, ry = 0.0, rrx = 0.0, rry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -988,284 +923,6 @@ void MSURF_Descriptor_Invoker::Get_MSURF_Descriptor_64(const cv::KeyPoint &kpt,
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method computes the upright G-SURF descriptor of the provided keypoint
* given the main orientation
* @param kpt Input keypoint
* @param desc Descriptor vector
* @note Rectangular grid of 20 s x 20 s. Descriptor Length 64. No additional
* G-SURF descriptor as described in Pablo F. Alcantarilla, Luis M. Bergasa and
* Andrew J. Davison, Gauge-SURF Descriptors, Image and Vision Computing 31(1), 2013
*/
void GSURF_Descriptor_Invoker::Get_GSURF_Upright_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
{
float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0;
float rx = 0.0, ry = 0.0, rxx = 0.0, rxy = 0.0, ryy = 0.0, len = 0.0, xf = 0.0, yf = 0.0;
float sample_x = 0.0, sample_y = 0.0;
float fx = 0.0, fy = 0.0, res1 = 0.0, res2 = 0.0, res3 = 0.0, res4 = 0.0;
float lvv = 0.0, lww = 0.0, modg = 0.0;
int x1 = 0, y1 = 0, x2 = 0, y2 = 0, sample_step = 0, pattern_size = 0, dcount = 0;
int dsize = 0, scale = 0, level = 0;
std::vector<TEvolution>& evolution_ = *_evolution;
// Set the descriptor size and the sample and pattern sizes
dsize = 64;
sample_step = 5;
pattern_size = 10;
// Get the information from the keypoint
yf = kpt.pt.y;
xf = kpt.pt.x;
scale = fRound(kpt.size / 2.0f);
level = kpt.class_id;
// Calculate descriptor for this interest point
for (int i = -pattern_size; i < pattern_size; i += sample_step) {
for (int j = -pattern_size; j < pattern_size; j += sample_step) {
dx = dy = mdx = mdy = 0.0;
for (int k = i; k < i + sample_step; k++) {
for (int l = j; l < j + sample_step; l++) {
// Get the coordinates of the sample point on the rotated axis
sample_y = yf + l*scale;
sample_x = xf + k*scale;
y1 = (int)(sample_y - 0.5f);
x1 = (int)(sample_x - 0.5f);
checkDescriptorLimits(x1, y1, options.img_width, options.img_height);
y2 = (int)(sample_y + 0.5f);
x2 = (int)(sample_x + 0.5f);
checkDescriptorLimits(x2, y2, options.img_width, options.img_height);
fx = sample_x - x1;
fy = sample_y - y1;
res1 = *(evolution_[level].Lx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lx.ptr<float>(y2)+x2);
rx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Ly.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Ly.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Ly.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Ly.ptr<float>(y2)+x2);
ry = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
modg = pow(rx, 2) + pow(ry, 2);
if (modg != 0.0) {
res1 = *(evolution_[level].Lxx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxx.ptr<float>(y2)+x2);
rxx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lxy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxy.ptr<float>(y2)+x2);
rxy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lyy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lyy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lyy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lyy.ptr<float>(y2)+x2);
ryy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
// Lww = (Lx^2 * Lxx + 2*Lx*Lxy*Ly + Ly^2*Lyy) / (Lx^2 + Ly^2)
lww = (pow(rx, 2)*rxx + 2.0f*rx*rxy*ry + pow(ry, 2)*ryy) / (modg);
// Lvv = (-2*Lx*Lxy*Ly + Lxx*Ly^2 + Lx^2*Lyy) / (Lx^2 + Ly^2)
lvv = (-2.0f*rx*rxy*ry + rxx*pow(ry, 2) + pow(rx, 2)*ryy) / (modg);
}
else {
lww = 0.0;
lvv = 0.0;
}
// Sum the derivatives to the cumulative descriptor
dx += lww;
dy += lvv;
mdx += fabs(lww);
mdy += fabs(lvv);
}
}
// Add the values to the descriptor vector
desc[dcount++] = dx;
desc[dcount++] = dy;
desc[dcount++] = mdx;
desc[dcount++] = mdy;
// Store the current length^2 of the vector
len += dx*dx + dy*dy + mdx*mdx + mdy*mdy;
}
}
// convert to unit vector
len = sqrt(len);
for (int i = 0; i < dsize; i++) {
desc[i] /= len;
}
if (options.use_clipping_normalilzation) {
clippingDescriptor(desc, dsize, options.clipping_normalization_niter, options.clipping_normalization_ratio);
}
}
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method computes the G-SURF descriptor of the provided keypoint given the
* main orientation
* @param kpt Input keypoint
* @param desc Descriptor vector
* @note Rectangular grid of 20 s x 20 s. Descriptor Length 64. No additional
* G-SURF descriptor as described in Pablo F. Alcantarilla, Luis M. Bergasa and
* Andrew J. Davison, Gauge-SURF Descriptors, Image and Vision Computing 31(1), 2013
*/
void GSURF_Descriptor_Invoker::Get_GSURF_Descriptor_64(const cv::KeyPoint &kpt, float *desc) const
{
float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0;
float rx = 0.0, ry = 0.0, rxx = 0.0, rxy = 0.0, ryy = 0.0, len = 0.0, xf = 0.0, yf = 0.0;
float sample_x = 0.0, sample_y = 0.0, co = 0.0, si = 0.0, angle = 0.0;
float fx = 0.0, fy = 0.0, res1 = 0.0, res2 = 0.0, res3 = 0.0, res4 = 0.0;
float lvv = 0.0, lww = 0.0, modg = 0.0;
int x1 = 0, y1 = 0, x2 = 0, y2 = 0, sample_step = 0, pattern_size = 0, dcount = 0;
int dsize = 0, scale = 0, level = 0;
std::vector<TEvolution>& evolution_ = *_evolution;
// Set the descriptor size and the sample and pattern sizes
dsize = 64;
sample_step = 5;
pattern_size = 10;
// Get the information from the keypoint
yf = kpt.pt.y;
xf = kpt.pt.x;
scale = fRound(kpt.size / 2.0f);
angle = kpt.angle;
level = kpt.class_id;
co = cos(angle);
si = sin(angle);
// Calculate descriptor for this interest point
for (int i = -pattern_size; i < pattern_size; i += sample_step) {
for (int j = -pattern_size; j < pattern_size; j += sample_step) {
dx = dy = mdx = mdy = 0.0;
for (int k = i; k < i + sample_step; k++) {
for (int l = j; l < j + sample_step; l++) {
// Get the coordinates of the sample point on the rotated axis
sample_y = yf + (l*scale*co + k*scale*si);
sample_x = xf + (-l*scale*si + k*scale*co);
y1 = (int)(sample_y - 0.5f);
x1 = (int)(sample_x - 0.5f);
checkDescriptorLimits(x1, y1, options.img_width, options.img_height);
y2 = (int)(sample_y + 0.5f);
x2 = (int)(sample_x + 0.5f);
checkDescriptorLimits(x2, y2, options.img_width, options.img_height);
fx = sample_x - x1;
fy = sample_y - y1;
res1 = *(evolution_[level].Lx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lx.ptr<float>(y2)+x2);
rx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Ly.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Ly.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Ly.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Ly.ptr<float>(y2)+x2);
ry = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
modg = pow(rx, 2) + pow(ry, 2);
if (modg != 0.0) {
res1 = *(evolution_[level].Lxx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxx.ptr<float>(y2)+x2);
rxx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lxy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxy.ptr<float>(y2)+x2);
rxy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lyy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lyy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lyy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lyy.ptr<float>(y2)+x2);
ryy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
// Lww = (Lx^2 * Lxx + 2*Lx*Lxy*Ly + Ly^2*Lyy) / (Lx^2 + Ly^2)
lww = (pow(rx, 2)*rxx + 2.0f*rx*rxy*ry + pow(ry, 2)*ryy) / (modg);
// Lvv = (-2*Lx*Lxy*Ly + Lxx*Ly^2 + Lx^2*Lyy) / (Lx^2 + Ly^2)
lvv = (-2.0f*rx*rxy*ry + rxx*pow(ry, 2) + pow(rx, 2)*ryy) / (modg);
}
else {
lww = 0.0;
lvv = 0.0;
}
// Sum the derivatives to the cumulative descriptor
dx += lww;
dy += lvv;
mdx += fabs(lww);
mdy += fabs(lvv);
}
}
// Add the values to the descriptor vector
desc[dcount++] = dx;
desc[dcount++] = dy;
desc[dcount++] = mdx;
desc[dcount++] = mdy;
// Store the current length^2 of the vector
len += dx*dx + dy*dy + mdx*mdx + mdy*mdy;
}
}
// convert to unit vector
len = sqrt(len);
for (int i = 0; i < dsize; i++) {
desc[i] /= len;
}
if (options.use_clipping_normalilzation) {
clippingDescriptor(desc, dsize, options.clipping_normalization_niter, options.clipping_normalization_ratio);
}
}
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method computes the extended upright descriptor (not rotation invariant) of
* the provided keypoint
@@ -1275,7 +932,7 @@ void GSURF_Descriptor_Invoker::Get_GSURF_Descriptor_64(const cv::KeyPoint &kpt,
* from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
* ECCV 2008
*/
void MSURF_Descriptor_Invoker::Get_MSURF_Upright_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
void KAZE_Descriptor_Invoker::Get_KAZE_Upright_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
{
float gauss_s1 = 0.0, gauss_s2 = 0.0;
float rx = 0.0, ry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -1433,7 +1090,7 @@ void MSURF_Descriptor_Invoker::Get_MSURF_Upright_Descriptor_128(const cv::KeyPoi
* from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
* ECCV 2008
*/
void MSURF_Descriptor_Invoker::Get_MSURF_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
void KAZE_Descriptor_Invoker::Get_KAZE_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
{
float gauss_s1 = 0.0, gauss_s2 = 0.0;
float rx = 0.0, ry = 0.0, rrx = 0.0, rry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -1587,322 +1244,6 @@ void MSURF_Descriptor_Invoker::Get_MSURF_Descriptor_128(const cv::KeyPoint &kpt,
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method computes the G-SURF upright extended descriptor
* (no rotation invariant) of the provided keypoint
* @param kpt Input keypoint
* @param desc Descriptor vector
* @note Rectangular grid of 20 s x 20 s. Descriptor Length 128. No additional
* G-SURF descriptor as described in Pablo F. Alcantarilla, Luis M. Bergasa and
* Andrew J. Davison, Gauge-SURF Descriptors, Image and Vision Computing 31(1), 2013
*/
void GSURF_Descriptor_Invoker::Get_GSURF_Upright_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
{
float len = 0.0, xf = 0.0, yf = 0.0, sample_x = 0.0, sample_y = 0.0;
float rx = 0.0, ry = 0.0, rxx = 0.0, rxy = 0.0, ryy = 0.0, modg = 0.0;
float fx = 0.0, fy = 0.0, res1 = 0.0, res2 = 0.0, res3 = 0.0, res4 = 0.0;
float dxp = 0.0, dyp = 0.0, mdxp = 0.0, mdyp = 0.0;
float dxn = 0.0, dyn = 0.0, mdxn = 0.0, mdyn = 0.0, lvv = 0.0, lww = 0.0;
int x1 = 0, y1 = 0, x2 = 0, y2 = 0, sample_step = 0, pattern_size = 0, dcount = 0;
int dsize = 0, scale = 0, level = 0;
std::vector<TEvolution>& evolution_ = *_evolution;
// Set the descriptor size and the sample and pattern sizes
dsize = 128;
sample_step = 5;
pattern_size = 10;
// Get the information from the keypoint
yf = kpt.pt.y;
xf = kpt.pt.x;
scale = fRound(kpt.size / 2.0f);
level = kpt.class_id;
// Calculate descriptor for this interest point
for (int i = -pattern_size; i < pattern_size; i += sample_step) {
for (int j = -pattern_size; j < pattern_size; j += sample_step) {
dxp = dxn = mdxp = mdxn = 0.0;
dyp = dyn = mdyp = mdyn = 0.0;
for (int k = i; k < i + sample_step; k++) {
for (int l = j; l < j + sample_step; l++) {
sample_y = k*scale + yf;
sample_x = l*scale + xf;
y1 = (int)(sample_y - 0.5f);
x1 = (int)(sample_x - 0.5f);
checkDescriptorLimits(x1, y1, options.img_width, options.img_height);
y2 = (int)(sample_y + 0.5f);
x2 = (int)(sample_x + 0.5f);
checkDescriptorLimits(x2, y2, options.img_width, options.img_height);
fx = sample_x - x1;
fy = sample_y - y1;
res1 = *(evolution_[level].Lx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lx.ptr<float>(y2)+x2);
rx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Ly.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Ly.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Ly.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Ly.ptr<float>(y2)+x2);
ry = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
modg = pow(rx, 2) + pow(ry, 2);
if (modg != 0.0) {
res1 = *(evolution_[level].Lxx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxx.ptr<float>(y2)+x2);
rxx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lxy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxy.ptr<float>(y2)+x2);
rxy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lyy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lyy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lyy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lyy.ptr<float>(y2)+x2);
ryy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
// Lww = (Lx^2 * Lxx + 2*Lx*Lxy*Ly + Ly^2*Lyy) / (Lx^2 + Ly^2)
lww = (pow(rx, 2)*rxx + 2.0f*rx*rxy*ry + pow(ry, 2)*ryy) / (modg);
// Lvv = (-2*Lx*Lxy*Ly + Lxx*Ly^2 + Lx^2*Lyy) / (Lx^2 + Ly^2)
lvv = (-2.0f*rx*rxy*ry + rxx*pow(ry, 2) + pow(rx, 2)*ryy) / (modg);
}
else {
lww = 0.0;
lvv = 0.0;
}
// Sum the derivatives to the cumulative descriptor
if (lww >= 0.0) {
dxp += lvv;
mdxp += fabs(lvv);
}
else {
dxn += lvv;
mdxn += fabs(lvv);
}
if (lvv >= 0.0) {
dyp += lww;
mdyp += fabs(lww);
}
else {
dyn += lww;
mdyn += fabs(lww);
}
}
}
// Add the values to the descriptor vector
desc[dcount++] = dxp;
desc[dcount++] = dxn;
desc[dcount++] = mdxp;
desc[dcount++] = mdxn;
desc[dcount++] = dyp;
desc[dcount++] = dyn;
desc[dcount++] = mdyp;
desc[dcount++] = mdyn;
// Store the current length^2 of the vector
len += dxp*dxp + dxn*dxn + mdxp*mdxp + mdxn*mdxn +
dyp*dyp + dyn*dyn + mdyp*mdyp + mdyn*mdyn;
}
}
// convert to unit vector
len = sqrt(len);
for (int i = 0; i < dsize; i++) {
desc[i] /= len;
}
if (options.use_clipping_normalilzation) {
clippingDescriptor(desc, dsize, options.clipping_normalization_niter, options.clipping_normalization_ratio);
}
}
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method computes the extended descriptor of the provided keypoint given the
* main orientation
* @param kpt Input keypoint
* @param desc Descriptor vector
* @note Rectangular grid of 20 s x 20 s. Descriptor Length 128. No additional
* G-SURF descriptor as described in Pablo F. Alcantarilla, Luis M. Bergasa and
* Andrew J. Davison, Gauge-SURF Descriptors, Image and Vision Computing 31(1), 2013
*/
void GSURF_Descriptor_Invoker::Get_GSURF_Descriptor_128(const cv::KeyPoint &kpt, float *desc) const
{
float len = 0.0, xf = 0.0, yf = 0.0;
float rx = 0.0, ry = 0.0, rxx = 0.0, rxy = 0.0, ryy = 0.0;
float sample_x = 0.0, sample_y = 0.0, co = 0.0, si = 0.0, angle = 0.0;
float fx = 0.0, fy = 0.0, res1 = 0.0, res2 = 0.0, res3 = 0.0, res4 = 0.0;
float dxp = 0.0, dyp = 0.0, mdxp = 0.0, mdyp = 0.0;
float dxn = 0.0, dyn = 0.0, mdxn = 0.0, mdyn = 0.0;
float lvv = 0.0, lww = 0.0, modg = 0.0;
int x1 = 0, y1 = 0, x2 = 0, y2 = 0, sample_step = 0, pattern_size = 0, dcount = 0;
int dsize = 0, scale = 0, level = 0;
std::vector<TEvolution>& evolution_ = *_evolution;
// Set the descriptor size and the sample and pattern sizes
dsize = 128;
sample_step = 5;
pattern_size = 10;
// Get the information from the keypoint
yf = kpt.pt.y;
xf = kpt.pt.x;
scale = fRound(kpt.size / 2.0f);
angle = kpt.angle;
level = kpt.class_id;
co = cos(angle);
si = sin(angle);
// Calculate descriptor for this interest point
for (int i = -pattern_size; i < pattern_size; i += sample_step) {
for (int j = -pattern_size; j < pattern_size; j += sample_step) {
dxp = dxn = mdxp = mdxn = 0.0;
dyp = dyn = mdyp = mdyn = 0.0;
for (int k = i; k < i + sample_step; k++) {
for (int l = j; l < j + sample_step; l++) {
// Get the coordinates of the sample point on the rotated axis
sample_y = yf + (l*scale*co + k*scale*si);
sample_x = xf + (-l*scale*si + k*scale*co);
y1 = (int)(sample_y - 0.5f);
x1 = (int)(sample_x - 0.5f);
checkDescriptorLimits(x1, y1, options.img_width, options.img_height);
y2 = (int)(sample_y + 0.5f);
x2 = (int)(sample_x + 0.5f);
checkDescriptorLimits(x2, y2, options.img_width, options.img_height);
fx = sample_x - x1;
fy = sample_y - y1;
res1 = *(evolution_[level].Lx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lx.ptr<float>(y2)+x2);
rx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Ly.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Ly.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Ly.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Ly.ptr<float>(y2)+x2);
ry = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
modg = pow(rx, 2) + pow(ry, 2);
if (modg != 0.0) {
res1 = *(evolution_[level].Lxx.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxx.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxx.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxx.ptr<float>(y2)+x2);
rxx = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lxy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lxy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lxy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lxy.ptr<float>(y2)+x2);
rxy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
res1 = *(evolution_[level].Lyy.ptr<float>(y1)+x1);
res2 = *(evolution_[level].Lyy.ptr<float>(y1)+x2);
res3 = *(evolution_[level].Lyy.ptr<float>(y2)+x1);
res4 = *(evolution_[level].Lyy.ptr<float>(y2)+x2);
ryy = (1.0f - fx)*(1.0f - fy)*res1 + fx*(1.0f - fy)*res2 + (1.0f - fx)*fy*res3 + fx*fy*res4;
// Lww = (Lx^2 * Lxx + 2*Lx*Lxy*Ly + Ly^2*Lyy) / (Lx^2 + Ly^2)
lww = (pow(rx, 2)*rxx + 2.0f*rx*rxy*ry + pow(ry, 2)*ryy) / (modg);
// Lvv = (-2*Lx*Lxy*Ly + Lxx*Ly^2 + Lx^2*Lyy) / (Lx^2 + Ly^2)
lvv = (-2.0f*rx*rxy*ry + rxx*pow(ry, 2) + pow(rx, 2)*ryy) / (modg);
}
else {
lww = 0.0;
lvv = 0.0;
}
// Sum the derivatives to the cumulative descriptor
if (lww >= 0.0) {
dxp += lvv;
mdxp += fabs(lvv);
}
else {
dxn += lvv;
mdxn += fabs(lvv);
}
if (lvv >= 0.0) {
dyp += lww;
mdyp += fabs(lww);
}
else {
dyn += lww;
mdyn += fabs(lww);
}
}
}
// Add the values to the descriptor vector
desc[dcount++] = dxp;
desc[dcount++] = dxn;
desc[dcount++] = mdxp;
desc[dcount++] = mdxn;
desc[dcount++] = dyp;
desc[dcount++] = dyn;
desc[dcount++] = mdyp;
desc[dcount++] = mdyn;
// Store the current length^2 of the vector
len += dxp*dxp + dxn*dxn + mdxp*mdxp + mdxn*mdxn +
dyp*dyp + dyn*dyn + mdyp*mdyp + mdyn*mdyn;
}
}
// convert to unit vector
len = sqrt(len);
for (int i = 0; i < dsize; i++) {
desc[i] /= len;
}
if (options.use_clipping_normalilzation) {
clippingDescriptor(desc, dsize, options.clipping_normalization_niter, options.clipping_normalization_ratio);
}
}
//*************************************************************************************
//*************************************************************************************
/**
* @brief This method performs a scalar non-linear diffusion step using AOS schemes
* @param Ld Image at a given evolution step
@@ -1911,7 +1252,7 @@ void GSURF_Descriptor_Invoker::Get_GSURF_Descriptor_128(const cv::KeyPoint &kpt,
* @param stepsize Stepsize for the nonlinear diffusion evolution
* @note If c is constant, the diffusion will be linear
* If c is a matrix of the same size as Ld, the diffusion will be nonlinear
* The stepsize can be arbitrarilly large
* The stepsize can be arbitrarily large
*/
void KAZEFeatures::AOS_Step_Scalar(cv::Mat &Ld, const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize) {

7
modules/features2d/test/test_keypoints.cpp
View File

@@ -169,11 +169,8 @@ TEST(Features2d_Detector_Keypoints_Dense, validation)
TEST(Features2d_Detector_Keypoints_KAZE, validation)
{
CV_FeatureDetectorKeypointsTest test_gsurf(cv::Ptr<FeatureDetector>(new cv::KAZE(cv::KAZE::DESCRIPTOR_GSURF, false, false)));
test_gsurf.safe_run();
CV_FeatureDetectorKeypointsTest test_msurf(cv::Ptr<FeatureDetector>(new cv::KAZE(cv::KAZE::DESCRIPTOR_MSURF, false, false)));
test_msurf.safe_run();
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.KAZE"));
test.safe_run();
}
TEST(Features2d_Detector_Keypoints_AKAZE, validation)