pnp_unittest.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */
#include <gtest/gtest.h>
#include <iostream>
#include <Eigen/Dense>
#include <mrpt/vision/pnp_algos.h>
 
// Opencv 2.3 had a broken <opencv/eigen.h> in Ubuntu 14.04 Trusty => Disable
// PNP classes
#include <mrpt/config.h>
#if MRPT_HAS_OPENCV && MRPT_OPENCV_VERSION_NUM < 0x240
#undef MRPT_HAS_OPENCV
#define MRPT_HAS_OPENCV 0
#endif
 
#if MRPT_HAS_OPENCV
 
class CPnPTest : public ::testing::Test
{
   public:
        mrpt::vision::pnp::CPnP cpnp;
 
        Eigen::MatrixXd obj_pts, img_pts, pose_est;
        Eigen::Matrix3d R, I3, R_est;
        Eigen::Vector3d t, t_est;
        int n;
 
        virtual void SetUp()
        {
                n = 6;
 
                obj_pts = Eigen::MatrixXd::Zero(3, n);
                img_pts = Eigen::MatrixXd::Zero(3, n);
                obj_pts << 0, 20, 10, 15, 14, 16, 0, 0, -10, -5, -2, -5, 0, 40, 0, 24,
                        21, 13;
 
                R << -0.3536, 0.3536, -0.8660, 0.9330, 0.0670, -0.3536, -0.0670,
                        -0.9330, -0.3536;
 
                t << 20, -30, 100;
 
                for (int i = 0; i < n; i++)
                {
                        img_pts.col(i) = (R * obj_pts.col(i) + t);
                        img_pts.col(i) /= img_pts(2, i);
                }
 
                I3 = Eigen::MatrixXd::Identity(3, 3);
 
                pose_est = Eigen::MatrixXd::Zero(6, 1);
        }
        virtual void TearDown() {}
};
 
TEST_F(CPnPTest, p3p_TEST)
{
        cpnp.p3p(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, rpnp_TEST)
{
        cpnp.rpnp(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, ppnp_TEST)
{
        cpnp.ppnp(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, posit_TEST)
{
        cpnp.posit(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, lhm_TEST)
{
        cpnp.lhm(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, dls_TEST)
{
        cpnp.dls(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, epnp_TEST)
{
        cpnp.epnp(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
TEST_F(CPnPTest, DISABLED_upnp_TEST)
{
        cpnp.upnp(obj_pts, img_pts, n, I3, pose_est);
 
        t_est << pose_est(0), pose_est(1), pose_est(2);
 
        double err_t = (t - t_est).norm();
 
        EXPECT_LE(err_t, 2);
}
 
#endif