Open Source Computer Vision Library https://opencv.org/
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// 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