C++ Pose3::transform_from方法代码示例

/* ************************************************************************* */
TEST( dataSet, writeBALfromValues_Dubrovnik){

  ///< Read a file using the unit tested readBAL
  const string filenameToRead = findExampleDataFile("dubrovnik-3-7-pre");
  SfM_data readData;
  readBAL(filenameToRead, readData);

  Pose3 poseChange = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.3,0.1,0.3));

  Values value;
  for(size_t i=0; i < readData.number_cameras(); i++){ // for each camera
    Key poseKey = symbol('x',i);
    Pose3 pose = poseChange.compose(readData.cameras[i].pose());
    value.insert(poseKey, pose);
  }
  for(size_t j=0; j < readData.number_tracks(); j++){ // for each point
    Key pointKey = P(j);
    Point3 point = poseChange.transform_from( readData.tracks[j].p );
    value.insert(pointKey, point);
  }

  // Write values and readData to a file
  const string filenameToWrite = createRewrittenFileName(filenameToRead);
  writeBALfromValues(filenameToWrite, readData, value);

  // Read the file we wrote
  SfM_data writtenData;
  readBAL(filenameToWrite, writtenData);

  // Check that the reprojection errors are the same and the poses are correct
  // Check number of things
  EXPECT_LONGS_EQUAL(3,writtenData.number_cameras());
  EXPECT_LONGS_EQUAL(7,writtenData.number_tracks());
  const SfM_Track& track0 = writtenData.tracks[0];
  EXPECT_LONGS_EQUAL(3,track0.number_measurements());

  // Check projection of a given point
  EXPECT_LONGS_EQUAL(0,track0.measurements[0].first);
  const SfM_Camera& camera0 = writtenData.cameras[0];
  Point2 expected = camera0.project(track0.p), actual = track0.measurements[0].second;
  EXPECT(assert_equal(expected,actual,12));

  Pose3 expectedPose = camera0.pose();
  Key poseKey = symbol('x',0);
  Pose3 actualPose = value.at<Pose3>(poseKey);
  EXPECT(assert_equal(expectedPose,actualPose, 1e-7));

  Point3 expectedPoint = track0.p;
  Key pointKey = P(0);
  Point3 actualPoint = value.at<Point3>(pointKey);
  EXPECT(assert_equal(expectedPoint,actualPoint, 1e-6));
}

int main(int argc, char** argv){

  Values initial_estimate;
  NonlinearFactorGraph graph;
  const noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(3,1);

  string calibration_loc = findExampleDataFile("VO_calibration.txt");
  string pose_loc = findExampleDataFile("VO_camera_poses_large.txt");
  string factor_loc = findExampleDataFile("VO_stereo_factors_large.txt");
  
  //read camera calibration info from file
  // focal lengths fx, fy, skew s, principal point u0, v0, baseline b
  double fx, fy, s, u0, v0, b;
  ifstream calibration_file(calibration_loc.c_str());
  cout << "Reading calibration info" << endl;
  calibration_file >> fx >> fy >> s >> u0 >> v0 >> b;

  //create stereo camera calibration object
  const Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(fx,fy,s,u0,v0,b));
  
  ifstream pose_file(pose_loc.c_str());
  cout << "Reading camera poses" << endl;
  int pose_id;
  MatrixRowMajor m(4,4);
  //read camera pose parameters and use to make initial estimates of camera poses
  while (pose_file >> pose_id) {
    for (int i = 0; i < 16; i++) {
      pose_file >> m.data()[i];
    }
    initial_estimate.insert(Symbol('x', pose_id), Pose3(m));
  }
  
  // camera and landmark keys
  size_t x, l;

  // pixel coordinates uL, uR, v (same for left/right images due to rectification)
  // landmark coordinates X, Y, Z in camera frame, resulting from triangulation
  double uL, uR, v, X, Y, Z;
  ifstream factor_file(factor_loc.c_str());
  cout << "Reading stereo factors" << endl;
  //read stereo measurement details from file and use to create and add GenericStereoFactor objects to the graph representation
  while (factor_file >> x >> l >> uL >> uR >> v >> X >> Y >> Z) {
    graph.push_back(
        GenericStereoFactor<Pose3, Point3>(StereoPoint2(uL, uR, v), model,
            Symbol('x', x), Symbol('l', l), K));
    //if the landmark variable included in this factor has not yet been added to the initial variable value estimate, add it
    if (!initial_estimate.exists(Symbol('l', l))) {
      Pose3 camPose = initial_estimate.at<Pose3>(Symbol('x', x));
      //transform_from() transforms the input Point3 from the camera pose space, camPose, to the global space
      Point3 worldPoint = camPose.transform_from(Point3(X, Y, Z));
      initial_estimate.insert(Symbol('l', l), worldPoint);
    }
  }

  Pose3 first_pose = initial_estimate.at<Pose3>(Symbol('x',1));
  //constrain the first pose such that it cannot change from its original value during optimization
  // NOTE: NonlinearEquality forces the optimizer to use QR rather than Cholesky
  // QR is much slower than Cholesky, but numerically more stable
  graph.push_back(NonlinearEquality<Pose3>(Symbol('x',1),first_pose));

  cout << "Optimizing" << endl;
  //create Levenberg-Marquardt optimizer to optimize the factor graph
  LevenbergMarquardtOptimizer optimizer = LevenbergMarquardtOptimizer(graph, initial_estimate);
  Values result = optimizer.optimize();

  cout << "Final result sample:" << endl;
  Values pose_values = result.filter<Pose3>();
  pose_values.print("Final camera poses:\n");

  return 0;
}