opencv/modules/3d/test/test_homography_decomp.cpp
Vadim Pisarevsky d6c699c014 calib3d module in opencv is split into 3 modules: 3d, calib and stereo.
stereo module in opencv_contrib is renamed to xstereo
2020-12-01 23:42:15 +03:00

170 lines
5.9 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
//
// This is a test file for the function decomposeHomography contributed to OpenCV
// by Samson Yilma.
//
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//
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// copy or use the software.
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// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2014, Samson Yilma (samson_yilma@yahoo.com), all rights reserved.
//
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//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class CV_HomographyDecompTest: public cvtest::BaseTest {
public:
CV_HomographyDecompTest()
{
buildTestDataSet();
}
protected:
void run(int)
{
vector<Mat> rotations;
vector<Mat> translations;
vector<Mat> normals;
decomposeHomographyMat(_H, _K, rotations, translations, normals);
//there should be at least 1 solution
ASSERT_GT(static_cast<int>(rotations.size()), 0);
ASSERT_GT(static_cast<int>(translations.size()), 0);
ASSERT_GT(static_cast<int>(normals.size()), 0);
ASSERT_EQ(rotations.size(), normals.size());
ASSERT_EQ(translations.size(), normals.size());
ASSERT_TRUE(containsValidMotion(rotations, translations, normals));
decomposeHomographyMat(_H, _K, rotations, noArray(), noArray());
ASSERT_GT(static_cast<int>(rotations.size()), 0);
}
private:
void buildTestDataSet()
{
_K = Matx33d(640, 0.0, 320,
0, 640, 240,
0, 0, 1);
_H = Matx33d(2.649157564634028, 4.583875997496426, 70.694447785121326,
-1.072756858861583, 3.533262150437228, 1513.656999614321649,
0.001303887589576, 0.003042206876298, 1.000000000000000
);
//expected solution for the given homography and intrinsic matrices
_R = Matx33d(0.43307983549125, 0.545749113549648, -0.717356090899523,
-0.85630229674426, 0.497582023798831, -0.138414255706431,
0.281404038139784, 0.67421809131173, 0.682818960388909);
_t = Vec3d(1.826751712278038, 1.264718492450820, 0.195080809998819);
_n = Vec3d(0.244875830334816, 0.480857890778889, 0.841909446789566);
}
bool containsValidMotion(std::vector<Mat>& rotations,
std::vector<Mat>& translations,
std::vector<Mat>& normals
)
{
double max_error = 1.0e-3;
vector<Mat>::iterator riter = rotations.begin();
vector<Mat>::iterator titer = translations.begin();
vector<Mat>::iterator niter = normals.begin();
for (;
riter != rotations.end() && titer != translations.end() && niter != normals.end();
++riter, ++titer, ++niter) {
double rdist = cvtest::norm(*riter, _R, NORM_INF);
double tdist = cvtest::norm(*titer, _t, NORM_INF);
double ndist = cvtest::norm(*niter, _n, NORM_INF);
if ( rdist < max_error
&& tdist < max_error
&& ndist < max_error )
return true;
}
return false;
}
Matx33d _R, _K, _H;
Vec3d _t, _n;
};
TEST(Calib3d_DecomposeHomography, regression) { CV_HomographyDecompTest test; test.safe_run(); }
TEST(Calib3d_DecomposeHomography, issue_4978)
{
Matx33d K(
1.0, 0.0, 0.0,
0.0, 1.0, 0.0,
0.0, 0.0, 1.0
);
Matx33d H(
-0.102896, 0.270191, -0.0031153,
0.0406387, 1.19569, -0.0120456,
0.445351, 0.0410889, 1
);
vector<Mat> rotations;
vector<Mat> translations;
vector<Mat> normals;
decomposeHomographyMat(H, K, rotations, translations, normals);
ASSERT_GT(rotations.size(), (size_t)0u);
for (size_t i = 0; i < rotations.size(); i++)
{
// check: det(R) = 1
EXPECT_TRUE(std::fabs(cv::determinant(rotations[i]) - 1.0) < 0.01)
<< "R: det=" << cv::determinant(rotations[0]) << std::endl << rotations[i] << std::endl
<< "T:" << std::endl << translations[i] << std::endl;
}
}
}} // namespace