reformulated irradiance to be: irradiance arround measured feature - irradiance at projection
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9c7f67d2fd
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05d277c4f4
@ -173,7 +173,7 @@ struct Feature {
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std::vector<double>& anchorPatch_estimate,
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IlluminationParameter& estimatedIllumination) const;
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bool MarkerGeneration(
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bool MarkerGeneration(
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ros::Publisher& marker_pub,
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const CamStateServer& cam_states) const;
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@ -183,6 +183,17 @@ bool MarkerGeneration(
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CameraCalibration& cam0,
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const std::vector<double> photo_r,
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std::stringstream& ss) const;
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/* @brief takes a pure pixel position (1m from image)
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* converts to actual pixel value and returns patch irradiance
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* around this pixel
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*/
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void PatchAroundPurePixel(cv::Point2f p,
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int N,
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const CameraCalibration& cam,
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const StateIDType& cam_state_id,
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std::vector<float>& return_i) const;
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/*
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* @brief projectPixelToPosition uses the calcualted pixels
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* of the anchor patch to generate 3D positions of all of em
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@ -665,6 +676,25 @@ bool Feature::VisualizePatch(
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cvWaitKey(0);
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}
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void Feature::PatchAroundPurePixel(cv::Point2f p,
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int N,
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const CameraCalibration& cam,
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const StateIDType& cam_state_id,
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std::vector<float>& return_i) const
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{
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int n = (int)(N-1)/2;
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cv::Mat image = cam.moving_window.find(cam_state_id)->second.image;
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cv::Point2f img_p = image_handler::distortPoint(p,
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cam.intrinsics,
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cam.distortion_model,
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cam.distortion_coeffs);
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for(double u_run = -n; u_run <= n; u_run++)
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for(double v_run = -n; v_run <= n; v_run++)
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return_i.push_back(PixelIrradiance(cv::Point2f(img_p.x+u_run, img_p.y+v_run), image));
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}
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float Feature::PixelIrradiance(cv::Point2f pose, cv::Mat image) const
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{
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@ -1229,51 +1229,28 @@ void MsckfVio::PhotometricMeasurementJacobian(
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Matrix3d R_w_c0 = quaternionToRotation(cam_state.orientation);
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const Vector3d& t_c0_w = cam_state.position;
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// Cam1 pose.
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Matrix3d R_c0_c1 = CAMState::T_cam0_cam1.linear();
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Matrix3d R_w_c1 = CAMState::T_cam0_cam1.linear() * R_w_c0;
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Vector3d t_c1_w = t_c0_w - R_w_c1.transpose()*CAMState::T_cam0_cam1.translation();
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//photometric observation
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std::vector<double> photo_z;
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// individual Jacobians
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Matrix<double, 1, 2> dI_dhj = Matrix<double, 1, 2>::Zero();
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Matrix<double, 2, 3> dh_dCpij = Matrix<double, 2, 3>::Zero();
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Matrix<double, 2, 3> dh_dGpij = Matrix<double, 2, 3>::Zero();
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Matrix<double, 2, 6> dh_dXplj = Matrix<double, 2, 6>::Zero();
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Matrix<double, 3, 1> dGpj_drhoj = Matrix<double, 3, 1>::Zero();
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Matrix<double, 3, 6> dGpj_XpAj = Matrix<double, 3, 6>::Zero();
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Matrix<double, 3, 3> dCpij_dGpij = Matrix<double, 3, 3>::Zero();
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Matrix<double, 3, 3> dCpij_dCGtheta = Matrix<double, 3, 3>::Zero();
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Matrix<double, 3, 3> dCpij_dGpC = Matrix<double, 3, 3>::Zero();
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// one line of the NxN Jacobians
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Eigen::Matrix<double, 1, 1> H_rhoj;
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Eigen::Matrix<double, 1, 6> H_plj;
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Eigen::Matrix<double, 1, 6> H_pAj;
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Matrix<double, 1, 6> H_xi;
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Matrix<double, 1, 3> H_fi;
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// combined Jacobians
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Eigen::MatrixXd H_rho(N*N, 1);
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Eigen::MatrixXd H_pl(N*N, 6);
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Eigen::MatrixXd H_pA(N*N, 6);
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MatrixXd H_xl = MatrixXd::Zero(feature.anchorPatch_3d.size(), 6);
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MatrixXd H_yl = MatrixXd::Zero(feature.anchorPatch_3d.size(), 3);
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auto frame = cam0.moving_window.find(cam_state_id)->second.image;
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int count = 0;
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double dx, dy;
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std::vector<float> z_irr_est;
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for (auto point : feature.anchorPatch_3d)
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{
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Eigen::Vector3d p_c0 = R_w_c0 * (point-t_c0_w);
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cv::Point2f p_in_c0 = feature.projectPositionToCamera(cam_state, cam_state_id, cam0, point);
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//add observation
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photo_z.push_back(feature.PixelIrradiance(p_in_c0, frame));
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z_irr_est.push_back(feature.PixelIrradiance(p_in_c0, frame));
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// add jacobian
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Matrix<double, 1, 2> dI_dhj = Matrix<double, 1, 2>::Zero();
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// frame derivative calculated convoluting with kernel [-1, 0, 1]
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dx = feature.PixelIrradiance(cv::Point2f(p_in_c0.x+1, p_in_c0.y), frame) - feature.PixelIrradiance(cv::Point2f(p_in_c0.x-1, p_in_c0.y), frame);
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@ -1281,111 +1258,45 @@ void MsckfVio::PhotometricMeasurementJacobian(
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dI_dhj(0, 0) = dx;
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dI_dhj(0, 1) = dy;
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//dh / d{}^Cp_{ij}
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dh_dCpij(0, 0) = 1 / p_c0(2);
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dh_dCpij(1, 1) = 1 / p_c0(2);
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dh_dCpij(0, 2) = -(p_c0(0))/(p_c0(2)*p_c0(2));
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dh_dCpij(1, 2) = -(p_c0(1))/(p_c0(2)*p_c0(2));
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// Compute the Jacobians.
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Matrix<double, 2, 3> dz_dpc0 = Matrix<double, 2, 3>::Zero();
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dz_dpc0(0, 0) = 1 / p_c0(2);
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dz_dpc0(1, 1) = 1 / p_c0(2);
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dz_dpc0(0, 2) = -p_c0(0) / (p_c0(2)*p_c0(2));
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dz_dpc0(1, 2) = -p_c0(1) / (p_c0(2)*p_c0(2));
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dCpij_dGpij = quaternionToRotation(cam_state.orientation);
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Matrix<double, 3, 6> dpc0_dxc = Matrix<double, 3, 6>::Zero();
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//orientation takes camera frame to world frame, we wa
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dh_dGpij = dh_dCpij * dCpij_dGpij;
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// original jacobi
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dpc0_dxc.leftCols(3) = skewSymmetric(p_c0);
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dpc0_dxc.rightCols(3) = -R_w_c0;
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//dh / d X_{pl}
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dCpij_dCGtheta = skewSymmetric(p_c0);
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dCpij_dGpC = -quaternionToRotation(cam_state.orientation);
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dh_dXplj.block<2, 3>(0, 0) = dh_dCpij * dCpij_dCGtheta;
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dh_dXplj.block<2, 3>(0, 3) = dh_dCpij * dCpij_dGpC;
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Matrix3d dpc0_dpg = R_w_c0;
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//d{}^Gp_P{ij} / \rho_i
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double rho = feature.anchor_rho;
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// Isometry T_anchor_w takes a vector in anchor frame to world frame
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dGpj_drhoj = -feature.T_anchor_w.linear() * Eigen::Vector3d(feature.anchorPatch_ideal[count].x/(rho*rho), feature.anchorPatch_ideal[count].y/(rho*rho), 1/(rho*rho));
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H_xi = dI_dhj*dz_dpc0*dpc0_dxc;
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H_fi = dI_dhj*dz_dpc0*dpc0_dpg;
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dGpj_XpAj.block<3, 3>(0, 0) = - feature.T_anchor_w.linear()
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* skewSymmetric(Eigen::Vector3d(feature.anchorPatch_ideal[count].x/(rho),
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feature.anchorPatch_ideal[count].y/(rho),
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1/(rho)));
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dGpj_XpAj.block<3, 3>(0, 3) = Matrix<double, 3, 3>::Identity();
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// Intermediate Jakobians
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H_rhoj = dI_dhj * dh_dGpij * dGpj_drhoj; // 1 x 1
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H_plj = dI_dhj * dh_dXplj; // 1 x 6
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H_pAj = dI_dhj * dh_dGpij * dGpj_XpAj; // 1 x 6
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H_rho.block<1, 1>(count, 0) = H_rhoj;
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H_pl.block<1, 6>(count, 0) = H_plj;
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H_pA.block<1, 6>(count, 0) = H_pAj;
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H_xl.block<1, 6>(count, 0) = H_xi;
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H_yl.block<1, 3>(count, 0) = H_fi;
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count++;
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}
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// calculate residual
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//observation
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const Vector4d& z = feature.observations.find(cam_state_id)->second;
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// Compute the residual.
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std::vector<float> z_irr;
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cv::Point2f z = cv::Point2f(feature.observations.find(cam_state_id)->second(0), feature.observations.find(cam_state_id)->second(1));
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feature.PatchAroundPurePixel(z, N, cam0, cam_state_id, z_irr);
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//estimate photometric measurement
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std::vector<double> estimate_irradiance;
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std::vector<double> estimate_photo_z;
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IlluminationParameter estimated_illumination;
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feature.estimate_FrameIrradiance(cam_state, cam_state_id, cam0, estimate_irradiance, estimated_illumination);
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Eigen::VectorXd r_l = Eigen::VectorXd::Zero(count-1);
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// calculated here, because we need true 'estimate_irradiance' later for jacobi
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for (auto& estimate_irradiance_j : estimate_irradiance)
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estimate_photo_z.push_back (estimate_irradiance_j *
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estimated_illumination.frame_gain * estimated_illumination.feature_gain +
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estimated_illumination.frame_bias + estimated_illumination.feature_bias);
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for(int i = 0; i < r_l.size(); i++)
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r_l(i) = z_irr[i]- z_irr_est[i];
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std::vector<double> photo_r;
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//calculate photom. residual
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for(int i = 0; i < photo_z.size(); i++)
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photo_r.push_back(photo_z[i] - estimate_photo_z[i]);
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MatrixXd H_xl = MatrixXd::Zero(N*N, 21+state_server.cam_states.size()*7);
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MatrixXd H_yl = MatrixXd::Zero(N*N, N*N+state_server.cam_states.size()+1);
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// set anchor Jakobi
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// get position of anchor in cam states
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auto cam_state_anchor = state_server.cam_states.find(feature.observations.begin()->first);
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int cam_state_cntr_anchor = std::distance(state_server.cam_states.begin(), cam_state_anchor);
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H_xl.block(0, 21+cam_state_cntr_anchor*7, N*N, 6) = -H_pA;
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// set frame Jakobi
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//get position of current frame in cam states
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auto cam_state_iter = state_server.cam_states.find(cam_state_id);
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int cam_state_cntr = std::distance(state_server.cam_states.begin(), cam_state_iter);
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// set jakobi of state
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H_xl.block(0, 21+cam_state_cntr*7, N*N, 6) = -H_pl;
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// set ones for irradiance bias
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H_xl.block(0, 21+cam_state_cntr*7+6, N*N, 1) = Eigen::ArrayXd::Ones(N*N);
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// set irradiance error Block
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H_yl.block(0, 0,N*N, N*N) = estimated_illumination.feature_gain * estimated_illumination.frame_gain * Eigen::MatrixXd::Identity(N*N, N*N);
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// TODO make this calculation more fluent
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for(int i = 0; i< N*N; i++)
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H_yl(i, N*N+cam_state_cntr) = estimate_irradiance[i];
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H_yl.block(0, N*N+state_server.cam_states.size(), N*N, 1) = -H_rho;
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r = r_l;
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H_x = H_xl;
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H_y = H_yl;
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//TODO make this more fluent as well
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count = 0;
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for(auto data : photo_r)
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r[count++] = data;
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std::stringstream ss;
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ss << "INFO:" << " anchor: " << cam_state_cntr_anchor << " frame: " << cam_state_cntr;
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if(PRINTIMAGES)
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{
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feature.MarkerGeneration(marker_pub, state_server.cam_states);
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feature.VisualizePatch(cam_state, cam_state_id, cam0, photo_r, ss);
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}
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// calculate residual
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return;
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}
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@ -1455,7 +1366,7 @@ void MsckfVio::PhotometricFeatureJacobian(
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state_server.cam_states.begin(), cam_state_iter);
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// Stack the Jacobians.
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H_xi.block(stack_cntr, 0, H_xl.rows(), H_xl.cols()) = H_xl;
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H_xi.block(stack_cntr, 21+cam_state_cntr*7, H_xl.rows(), H_xl.cols()) = H_xl;
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H_yi.block(stack_cntr, 0, H_yl.rows(), H_yl.cols()) = H_yl;
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r_i.segment(stack_cntr, N*N) = r_l;
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stack_cntr += N*N;
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@ -1500,8 +1411,7 @@ void MsckfVio::PhotometricFeatureJacobian(
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void MsckfVio::measurementJacobian(
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const StateIDType& cam_state_id,
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const FeatureIDType& feature_id,
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Matrix<double, 4, 6>& H_x, Matrix<double, 4, 3>& H_f, Vector4d& r)
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{
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Matrix<double, 4, 6>& H_x, Matrix<double, 4, 3>& H_f, Vector4d& r) {
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// Prepare all the required data.
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const CAMState& cam_state = state_server.cam_states[cam_state_id];
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@ -1540,8 +1450,6 @@ void MsckfVio::measurementJacobian(
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dz_dpc1(3, 2) = -p_c1(1) / (p_c1(2)*p_c1(2));
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Matrix<double, 3, 6> dpc0_dxc = Matrix<double, 3, 6>::Zero();
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// original jacobi
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dpc0_dxc.leftCols(3) = skewSymmetric(p_c0);
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dpc0_dxc.rightCols(3) = -R_w_c0;
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@ -1555,6 +1463,17 @@ void MsckfVio::measurementJacobian(
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H_x = dz_dpc0*dpc0_dxc + dz_dpc1*dpc1_dxc;
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H_f = dz_dpc0*dpc0_dpg + dz_dpc1*dpc1_dpg;
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// Modifty the measurement Jacobian to ensure
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// observability constrain.
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Matrix<double, 4, 6> A = H_x;
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Matrix<double, 6, 1> u = Matrix<double, 6, 1>::Zero();
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u.block<3, 1>(0, 0) = quaternionToRotation(
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cam_state.orientation_null) * IMUState::gravity;
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u.block<3, 1>(3, 0) = skewSymmetric(
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p_w-cam_state.position_null) * IMUState::gravity;
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H_x = A - A*u*(u.transpose()*u).inverse()*u.transpose();
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H_f = -H_x.block<4, 3>(0, 3);
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// Compute the residual.
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r = z - Vector4d(p_c0(0)/p_c0(2), p_c0(1)/p_c0(2),
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p_c1(0)/p_c1(2), p_c1(1)/p_c1(2));
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@ -1562,6 +1481,7 @@ void MsckfVio::measurementJacobian(
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return;
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}
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void MsckfVio::featureJacobian(
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const FeatureIDType& feature_id,
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const std::vector<StateIDType>& cam_state_ids,
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@ -1853,6 +1773,12 @@ void MsckfVio::removeLostFeatures() {
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else
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featureJacobian(feature.id, cam_state_ids, H_xj, r_j);
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cout << "\n" << endl;
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cout << "H_xj: \n" << H_xj << endl;
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cout << "res: \n" << endl;
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cout << r_j << endl;
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if (gatingTest(H_xj, r_j, cam_state_ids.size()-1)) {
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H_x.block(stack_cntr, 0, H_xj.rows(), H_xj.cols()) = H_xj;
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r.segment(stack_cntr, r_j.rows()) = r_j;
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@ -2015,6 +1941,12 @@ void MsckfVio::pruneCamStateBuffer() {
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else
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featureJacobian(feature.id, involved_cam_state_ids, H_xj, r_j);
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cout << "\n" << endl;
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cout << "H_xj: \n" << H_xj << endl;
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cout << "res: \n" << endl;
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cout << r_j << endl;
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if (gatingTest(H_xj, r_j, involved_cam_state_ids.size())) {
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H_x.block(stack_cntr, 0, H_xj.rows(), H_xj.cols()) = H_xj;
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r.segment(stack_cntr, r_j.rows()) = r_j;
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