colmap/src/estimators/absolute_pose_test.cc

// Copyright (c) 2022, ETH Zurich and UNC Chapel Hill.
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// Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

#define TEST_NAME "base/absolute_pose"
#include "util/testing.h"

#include <Eigen/Core>

#include "base/pose.h"
#include "base/similarity_transform.h"
#include "estimators/absolute_pose.h"
#include "estimators/essential_matrix.h"
#include "optim/ransac.h"
#include "util/random.h"

using namespace colmap;

BOOST_AUTO_TEST_CASE(TestP3P) {
  SetPRNGSeed(0);

  std::vector<Eigen::Vector3d> points3D;
  points3D.emplace_back(1, 1, 1);
  points3D.emplace_back(0, 1, 1);
  points3D.emplace_back(3, 1.0, 4);
  points3D.emplace_back(3, 1.1, 4);
  points3D.emplace_back(3, 1.2, 4);
  points3D.emplace_back(3, 1.3, 4);
  points3D.emplace_back(3, 1.4, 4);
  points3D.emplace_back(2, 1, 7);

  auto points3D_faulty = points3D;
  for (size_t i = 0; i < points3D.size(); ++i) {
    points3D_faulty[i](0) = 20;
  }

  for (double qx = 0; qx < 1; qx += 0.2) {
    for (double tx = 0; tx < 1; tx += 0.1) {
      const SimilarityTransform3 orig_tform(1, Eigen::Vector4d(1, qx, 0, 0),
                                            Eigen::Vector3d(tx, 0, 0));

      // Project points to camera coordinate system.
      std::vector<Eigen::Vector2d> points2D;
      for (size_t i = 0; i < points3D.size(); ++i) {
        Eigen::Vector3d point3D_camera = points3D[i];
        orig_tform.TransformPoint(&point3D_camera);
        points2D.push_back(point3D_camera.hnormalized());
      }

      RANSACOptions options;
      options.max_error = 1e-5;
      RANSAC<P3PEstimator> ransac(options);
      const auto report = ransac.Estimate(points2D, points3D);

      BOOST_CHECK_EQUAL(report.success, true);

      // Test if correct transformation has been determined.
      const double matrix_diff =
          (orig_tform.Matrix().topLeftCorner<3, 4>() - report.model).norm();
      BOOST_CHECK(matrix_diff < 1e-2);

      // Test residuals of exact points.
      std::vector<double> residuals;
      P3PEstimator::Residuals(points2D, points3D, report.model, &residuals);
      for (size_t i = 0; i < residuals.size(); ++i) {
        BOOST_CHECK(residuals[i] < 1e-3);
      }

      // Test residuals of faulty points.
      P3PEstimator::Residuals(points2D, points3D_faulty, report.model,
                              &residuals);
      for (size_t i = 0; i < residuals.size(); ++i) {
        BOOST_CHECK(residuals[i] > 0.1);
      }
    }
  }
}

BOOST_AUTO_TEST_CASE(TestEPNP) {
  SetPRNGSeed(0);

  std::vector<Eigen::Vector3d> points3D;
  points3D.emplace_back(1, 1, 1);
  points3D.emplace_back(0, 1, 1);
  points3D.emplace_back(3, 1.0, 4);
  points3D.emplace_back(3, 1.1, 4);
  points3D.emplace_back(3, 1.2, 4);
  points3D.emplace_back(3, 1.3, 4);
  points3D.emplace_back(3, 1.4, 4);
  points3D.emplace_back(2, 1, 7);

  auto points3D_faulty = points3D;
  for (size_t i = 0; i < points3D.size(); ++i) {
    points3D_faulty[i](0) = 20;
  }

  for (double qx = 0; qx < 1; qx += 0.2) {
    for (double tx = 0; tx < 1; tx += 0.1) {
      const SimilarityTransform3 orig_tform(1, Eigen::Vector4d(1, qx, 0, 0),
                                            Eigen::Vector3d(tx, 0, 0));

      // Project points to camera coordinate system.
      std::vector<Eigen::Vector2d> points2D;
      for (size_t i = 0; i < points3D.size(); ++i) {
        Eigen::Vector3d point3D_camera = points3D[i];
        orig_tform.TransformPoint(&point3D_camera);
        points2D.push_back(point3D_camera.hnormalized());
      }

      RANSACOptions options;
      options.max_error = 1e-5;
      RANSAC<EPNPEstimator> ransac(options);
      const auto report = ransac.Estimate(points2D, points3D);

      BOOST_CHECK_EQUAL(report.success, true);

      // Test if correct transformation has been determined.
      const double matrix_diff =
          (orig_tform.Matrix().topLeftCorner<3, 4>() - report.model).norm();
      BOOST_CHECK(matrix_diff < 1e-3);

      // Test residuals of exact points.
      std::vector<double> residuals;
      EPNPEstimator::Residuals(points2D, points3D, report.model, &residuals);
      for (size_t i = 0; i < residuals.size(); ++i) {
        BOOST_CHECK(residuals[i] < 1e-3);
      }

      // Test residuals of faulty points.
      EPNPEstimator::Residuals(points2D, points3D_faulty, report.model,
                               &residuals);
      for (size_t i = 0; i < residuals.size(); ++i) {
        BOOST_CHECK(residuals[i] > 0.1);
      }
    }
  }
}

BOOST_AUTO_TEST_CASE(TestEPNP_BrokenSolveSignCase) {
  std::vector<Eigen::Vector2d> points2D;
  points2D.emplace_back(-2.6783007931074532e-01, 5.3457197430746251e-01);
  points2D.emplace_back(-4.2629907287470264e-01, 7.5623350319519789e-01);
  points2D.emplace_back(-1.6767413005963930e-01, -1.3387172544910089e-01);
  points2D.emplace_back(-5.6616329720373559e-02, 2.3621156497739373e-01);
  points2D.emplace_back(-1.7721225948969935e-01, 2.3395366792735982e-02);
  points2D.emplace_back(-5.1836259886632222e-02, -4.4380694271927049e-02);
  points2D.emplace_back(-3.5897765845560037e-01, 1.6252721078589397e-01);
  points2D.emplace_back(2.7057324473684058e-01, -1.4067450104631887e-01);
  points2D.emplace_back(-2.5811166424334520e-01, 8.0167171300227366e-02);
  points2D.emplace_back(2.0239567448222310e-02, -3.2845953375344145e-01);
  points2D.emplace_back(4.2571014715170657e-01, -2.8321173570154773e-01);
  points2D.emplace_back(-5.4597596412987237e-01, 9.1431935871671977e-02);

  std::vector<Eigen::Vector3d> points3D;
  points3D.emplace_back(4.4276865308679305e+00, -1.3384364366019632e+00,
                        -3.5997423085253892e+00);
  points3D.emplace_back(2.7278555252512309e+00, -3.8152996187231392e-01,
                        -2.6558518399902824e+00);
  points3D.emplace_back(4.8548566083054894e+00, -1.4756197433631739e+00,
                        -6.8274946022490501e-01);
  points3D.emplace_back(3.1523013527998449e+00, -1.3377020437938025e+00,
                        -1.6443269301929087e+00);
  points3D.emplace_back(3.8551679771512073e+00, -1.0557700545885551e+00,
                        -1.1695994508851486e+00);
  points3D.emplace_back(5.9571373150353812e+00, -2.6120646101684555e+00,
                        -1.0841441206050342e+00);
  points3D.emplace_back(6.3287088499358894e+00, -1.1761274755817175e+00,
                        -2.5951879774151583e+00);
  points3D.emplace_back(2.3005305990121250e+00, -1.4019796626800123e+00,
                        -4.4485464455072321e-01);
  points3D.emplace_back(5.9816859934587354e+00, -1.4211814511691452e+00,
                        -2.0285923889293449e+00);
  points3D.emplace_back(5.2543344690665457e+00, -2.3389255564264144e+00,
                        4.3708173185524052e-01);
  points3D.emplace_back(3.2181599245991688e+00, -2.8906671988445098e+00,
                        2.6825718150064348e-01);
  points3D.emplace_back(4.4592895306946758e+00, -9.1235241641579902e-03,
                        -1.6555237117970871e+00);

  const std::vector<EPNPEstimator::M_t> output =
      EPNPEstimator::Estimate(points2D, points3D);

  BOOST_CHECK_EQUAL(output.size(), 1);

  double reproj = 0.0;
  for (size_t i = 0; i < points3D.size(); ++i) {
    reproj +=
        ((output[0] * points3D[i].homogeneous()).hnormalized() - points2D[i])
            .norm();
  }

  BOOST_CHECK(reproj < 0.2);
}