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Merge pull request opencv#16614 from GFleishman:estimateTranslation3D
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added estimateTranslation3D to calib3d/ptsetreg

* added estimateTranslation3D; follows API and implementation structure for estimateAffine3D, but only allows for translation

* void variables in null function to suppress compiler warnings

* added test for estimateTranslation3D

* changed to Matx13d datatype for translation vector in ptsetreg and test; used short license in test

* removed iostream include

* calib3d: code cleanup
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GFleishman authored Apr 7, 2020
1 parent 0c2a439 commit 31ec9b2
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47 changes: 47 additions & 0 deletions modules/calib3d/include/opencv2/calib3d.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -2869,6 +2869,53 @@ CV_EXPORTS_W int estimateAffine3D(InputArray src, InputArray dst,
OutputArray out, OutputArray inliers,
double ransacThreshold = 3, double confidence = 0.99);

/** @brief Computes an optimal translation between two 3D point sets.
*
* It computes
* \f[
* \begin{bmatrix}
* x\\
* y\\
* z\\
* \end{bmatrix}
* =
* \begin{bmatrix}
* X\\
* Y\\
* Z\\
* \end{bmatrix}
* +
* \begin{bmatrix}
* b_1\\
* b_2\\
* b_3\\
* \end{bmatrix}
* \f]
*
* @param src First input 3D point set containing \f$(X,Y,Z)\f$.
* @param dst Second input 3D point set containing \f$(x,y,z)\f$.
* @param out Output 3D translation vector \f$3 \times 1\f$ of the form
* \f[
* \begin{bmatrix}
* b_1 \\
* b_2 \\
* b_3 \\
* \end{bmatrix}
* \f]
* @param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier).
* @param ransacThreshold Maximum reprojection error in the RANSAC algorithm to consider a point as
* an inlier.
* @param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything
* between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation
* significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
*
* The function estimates an optimal 3D translation between two 3D point sets using the
* RANSAC algorithm.
* */
CV_EXPORTS_W int estimateTranslation3D(InputArray src, InputArray dst,
OutputArray out, OutputArray inliers,
double ransacThreshold = 3, double confidence = 0.99);

/** @brief Computes an optimal affine transformation between two 2D point sets.
It computes
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104 changes: 104 additions & 0 deletions modules/calib3d/src/ptsetreg.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -505,6 +505,86 @@ class Affine3DEstimatorCallback : public PointSetRegistrator::Callback
}
};


/*
* Compute
* x X t1
* y = Y + t2
* z Z t3
*
* - every element in _m1 contains (X,Y,Z), which are called source points
* - every element in _m2 contains (x,y,z), which are called destination points
* - _model is of size 3x1, which contains
* t1
* t2
* t3
*/
class Translation3DEstimatorCallback CV_FINAL : public PointSetRegistrator::Callback
{
public:
int runKernel( InputArray _m1, InputArray _m2, OutputArray _model ) const CV_OVERRIDE
{

Mat m1 = _m1.getMat(), m2 = _m2.getMat();
const Point3f* from = m1.ptr<Point3f>();
const Point3f* to = m2.ptr<Point3f>();

Matx13d T;

// The optimal translation is the mean of the pointwise displacements
for(int i = 0; i < 4; i++)
{
const Point3f& f = from[i];
const Point3f& t = to[i];

T(0, 0) = T(0, 0) + t.x - f.x;
T(0, 1) = T(0, 1) + t.y - f.y;
T(0, 2) = T(0, 2) + t.z - f.z;
}
T *= (1.0f / 4);
Mat(T, false).copyTo(_model);
return 1;
}

void computeError( InputArray _m1, InputArray _m2, InputArray _model, OutputArray _err ) const CV_OVERRIDE
{
Mat m1 = _m1.getMat(), m2 = _m2.getMat(), model = _model.getMat();
const Point3f* from = m1.ptr<Point3f>();
const Point3f* to = m2.ptr<Point3f>();
const double* F = model.ptr<double>();

int count = m1.checkVector(3);
CV_Assert( count > 0 );

_err.create(count, 1, CV_32F);
Mat err = _err.getMat();
float* errptr = err.ptr<float>();

for(int i = 0; i < count; i++ )
{
const Point3f& f = from[i];
const Point3f& t = to[i];

double a = F[0] + f.x - t.x;
double b = F[1] + f.y - t.y;
double c = F[2] + f.z - t.z;

errptr[i] = (float)(a*a + b*b + c*c);
}
}

// not doing SVD, no degeneracy concerns, can simply return true
bool checkSubset( InputArray _ms1, InputArray _ms2, int count ) const CV_OVERRIDE
{
// voids to suppress compiler warnings
(void)_ms1;
(void)_ms2;
(void)count;
return true;
}
};


/*
* Compute
* x a b X c
Expand Down Expand Up @@ -818,6 +898,30 @@ int estimateAffine3D(InputArray _from, InputArray _to,
return createRANSACPointSetRegistrator(makePtr<Affine3DEstimatorCallback>(), 4, ransacThreshold, confidence)->run(dFrom, dTo, _out, _inliers);
}

int estimateTranslation3D(InputArray _from, InputArray _to,
OutputArray _out, OutputArray _inliers,
double ransacThreshold, double confidence)
{
CV_INSTRUMENT_REGION();

Mat from = _from.getMat(), to = _to.getMat();
int count = from.checkVector(3);

CV_Assert( count >= 0 && to.checkVector(3) == count );

Mat dFrom, dTo;
from.convertTo(dFrom, CV_32F);
to.convertTo(dTo, CV_32F);
dFrom = dFrom.reshape(3, count);
dTo = dTo.reshape(3, count);

const double epsilon = DBL_EPSILON;
ransacThreshold = ransacThreshold <= 0 ? 3 : ransacThreshold;
confidence = (confidence < epsilon) ? 0.99 : (confidence > 1 - epsilon) ? 0.99 : confidence;

return createRANSACPointSetRegistrator(makePtr<Translation3DEstimatorCallback>(), 4, ransacThreshold, confidence)->run(dFrom, dTo, _out, _inliers);
}

Mat estimateAffine2D(InputArray _from, InputArray _to, OutputArray _inliers,
const int method, const double ransacReprojThreshold,
const size_t maxIters, const double confidence,
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100 changes: 100 additions & 0 deletions modules/calib3d/test/test_translation3d_estimator.cpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,100 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.


#include "test_precomp.hpp"

namespace opencv_test { namespace {

TEST(Calib3d_EstimateTranslation3D, test4Points)
{
Matx13d trans;
cv::randu(trans, Scalar(1), Scalar(3));

// setting points that are no in the same line

Mat fpts(1, 4, CV_32FC3);
Mat tpts(1, 4, CV_32FC3);

RNG& rng = theRNG();
fpts.at<Point3f>(0) = Point3f(rng.uniform(1.0f, 2.0f), rng.uniform(1.0f, 2.0f), rng.uniform(5.0f, 6.0f));
fpts.at<Point3f>(1) = Point3f(rng.uniform(3.0f, 4.0f), rng.uniform(3.0f, 4.0f), rng.uniform(5.0f, 6.0f));
fpts.at<Point3f>(2) = Point3f(rng.uniform(1.0f, 2.0f), rng.uniform(3.0f, 4.0f), rng.uniform(5.0f, 6.0f));
fpts.at<Point3f>(3) = Point3f(rng.uniform(3.0f, 4.0f), rng.uniform(1.0f, 2.0f), rng.uniform(5.0f, 6.0f));

std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + 4, tpts.ptr<Point3f>(),
[&] (const Point3f& p) -> Point3f
{
return Point3f((float)(p.x + trans(0, 0)),
(float)(p.y + trans(0, 1)),
(float)(p.z + trans(0, 2)));
}
);

Matx13d trans_est;
vector<uchar> outliers;
int res = estimateTranslation3D(fpts, tpts, trans_est, outliers);
EXPECT_GT(res, 0);

const double thres = 1e-3;

EXPECT_LE(cvtest::norm(trans_est, trans, NORM_INF), thres)
<< "aff est: " << trans_est << endl
<< "aff ref: " << trans;
}

TEST(Calib3d_EstimateTranslation3D, testNPoints)
{
Matx13d trans;
cv::randu(trans, Scalar(-2), Scalar(2));

// setting points that are no in the same line

const int n = 100;
const int m = 3*n/5;
const Point3f shift_outl = Point3f(15, 15, 15);
const float noise_level = 20.f;

Mat fpts(1, n, CV_32FC3);
Mat tpts(1, n, CV_32FC3);

randu(fpts, Scalar::all(0), Scalar::all(100));
std::transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + n, tpts.ptr<Point3f>(),
[&] (const Point3f& p) -> Point3f
{
return Point3f((float)(p.x + trans(0, 0)),
(float)(p.y + trans(0, 1)),
(float)(p.z + trans(0, 2)));
}
);

/* adding noise*/
std::transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m,
[&] (const Point3f& pt) -> Point3f
{
Point3f p = pt + shift_outl;
RNG& rng = theRNG();
return Point3f(p.x + noise_level * (float)rng,
p.y + noise_level * (float)rng,
p.z + noise_level * (float)rng);
}
);

Matx13d trans_est;
vector<uchar> outl;
int res = estimateTranslation3D(fpts, tpts, trans_est, outl);
EXPECT_GT(res, 0);

const double thres = 1e-4;
EXPECT_LE(cvtest::norm(trans_est, trans, NORM_INF), thres)
<< "aff est: " << trans_est << endl
<< "aff ref: " << trans;

bool outl_good = count(outl.begin(), outl.end(), 1) == m &&
m == accumulate(outl.begin(), outl.begin() + m, 0);

EXPECT_TRUE(outl_good);
}

}} // namespace

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