Implemented custom intrinsic matrix undistortion.
This commit is contained in:
Daniel
@ -123,22 +123,372 @@ CameraInternal::CameraInternal(const Camera &cam)
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{
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this->cam = cam;
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// Convert camera matrix to cv::Mat for OpenCV
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K = cv::Mat(3, 3, CV_32FC1, const_cast<float *>(&cam.K[0][0])).clone();
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DC = cv::Mat(cam.DC.size(), 1, CV_32FC1, const_cast<float *>(cam.DC.data())).clone();
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R = cv::Mat(3, 3, CV_32FC1, const_cast<float *>(&cam.R[0][0])).clone();
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T = cv::Mat(3, 1, CV_32FC1, const_cast<float *>(&cam.T[0][0])).clone();
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this->invK = invert3x3(cam.K);
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this->invR = transpose3x3(cam.R);
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// Camera center:
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// C = -(Rᵀ * t) = -(Rᵀ * (R * (T * -1))) = -(Rᵀ * (R * -T)) = -(Rᵀ * -R * T) = -(-T) = T
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this->center = {cam.T[0][0], cam.T[1][0], cam.T[2][0]};
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}
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// =================================================================================================
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void CameraInternal::update_projection_matrix()
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std::array<std::array<float, 3>, 3> CameraInternal::transpose3x3(
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const std::array<std::array<float, 3>, 3> &M)
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{
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// Calculate opencv-style projection matrix
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cv::Mat Tr, RT;
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Tr = R * (T * -1);
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cv::hconcat(R, Tr, RT);
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P = K * RT;
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return {{{M[0][0], M[1][0], M[2][0]},
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{M[0][1], M[1][1], M[2][1]},
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{M[0][2], M[1][2], M[2][2]}}};
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}
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// =================================================================================================
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std::array<std::array<float, 3>, 3> CameraInternal::invert3x3(
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const std::array<std::array<float, 3>, 3> &M)
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{
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// Compute the inverse using the adjugate method
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// See: https://scicomp.stackexchange.com/a/29206
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std::array<std::array<float, 3>, 3> adj = {
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{{
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M[1][1] * M[2][2] - M[1][2] * M[2][1],
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M[0][2] * M[2][1] - M[0][1] * M[2][2],
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M[0][1] * M[1][2] - M[0][2] * M[1][1],
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},
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{
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M[1][2] * M[2][0] - M[1][0] * M[2][2],
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M[0][0] * M[2][2] - M[0][2] * M[2][0],
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M[0][2] * M[1][0] - M[0][0] * M[1][2],
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},
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{
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M[1][0] * M[2][1] - M[1][1] * M[2][0],
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M[0][1] * M[2][0] - M[0][0] * M[2][1],
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M[0][0] * M[1][1] - M[0][1] * M[1][0],
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}}};
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float det = M[0][0] * adj[0][0] + M[0][1] * adj[1][0] + M[0][2] * adj[2][0];
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if (std::fabs(det) < 1e-6f)
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{
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return {{{0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}}};
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}
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float idet = 1.0f / det;
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std::array<std::array<float, 3>, 3> inv = {
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{{
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adj[0][0] * idet,
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adj[0][1] * idet,
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adj[0][2] * idet,
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},
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{
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adj[1][0] * idet,
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adj[1][1] * idet,
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adj[1][2] * idet,
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},
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{
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adj[2][0] * idet,
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adj[2][1] * idet,
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adj[2][2] * idet,
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}}};
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return inv;
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}
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// =================================================================================================
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void CameraInternal::undistort_point_pinhole(std::array<float, 3> &p, const std::vector<float> &k)
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{
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// Following: cv::cvUndistortPointsInternal
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// Uses only the distortion coefficients: [k1, k2, p1, p2, k3]
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// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/undistort.dispatch.cpp#L432
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float x0 = p[0];
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float y0 = p[1];
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float x = x0;
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float y = y0;
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// Iteratively refine the estimate for the undistorted point.
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int max_iterations = 5;
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for (int iter = 0; iter < max_iterations; ++iter)
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{
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float r2 = x * x + y * y;
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double icdist = 1.0 / (1 + ((k[4] * r2 + k[1]) * r2 + k[0]) * r2);
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if (icdist < 0)
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{
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x = x0;
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y = y0;
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break;
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}
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float deltaX = 2 * k[2] * x * y + k[3] * (r2 + 2 * x * x);
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float deltaY = k[2] * (r2 + 2 * y * y) + 2 * k[3] * x * y;
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x = (x0 - deltaX) * icdist;
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y = (y0 - deltaY) * icdist;
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}
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p[0] = x;
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p[1] = y;
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}
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// =================================================================================================
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void CameraInternal::undistort_point_fisheye(std::array<float, 3> &p, const std::vector<float> &k)
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{
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// Following: cv::fisheye::undistortPoints
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// Uses only the distortion coefficients: [k1, k2, k3, k4]
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// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/fisheye.cpp#L429
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float theta_d = std::sqrt(p[0] * p[0] + p[1] * p[1]);
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float pi_half = std::numbers::pi * 0.5;
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theta_d = std::min(std::max(-pi_half, theta_d), pi_half);
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if (theta_d < 1e-6)
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{
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return;
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}
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float scale = 0.0;
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float theta = theta_d;
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int max_iterations = 5;
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for (int iter = 0; iter < max_iterations; ++iter)
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{
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float theta2 = theta * theta;
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float theta4 = theta2 * theta2;
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float theta6 = theta4 * theta2;
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float theta8 = theta4 * theta4;
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float k0_theta2 = k[0] * theta2;
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float k1_theta4 = k[1] * theta4;
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float k2_theta6 = k[2] * theta6;
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float k3_theta8 = k[3] * theta8;
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float theta_fix = (theta * (1 + k0_theta2 + k1_theta4 + k2_theta6 + k3_theta8) - theta_d) /
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(1 + 3 * k0_theta2 + 5 * k1_theta4 + 7 * k2_theta6 + 9 * k3_theta8);
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theta = theta - theta_fix;
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if (std::fabs(theta_fix) < 1e-6)
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{
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break;
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}
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}
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scale = std::tan(theta) / theta_d;
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p[0] *= scale;
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p[1] *= scale;
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}
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// =================================================================================================
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std::array<std::array<float, 3>, 3> CameraInternal::calc_optimal_camera_matrix_fisheye(
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float balance, std::pair<int, int> new_size)
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{
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// Following: cv::fisheye::estimateNewCameraMatrixForUndistortRectify
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// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/fisheye.cpp#L630
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float fov_scale = 1.0;
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float w = static_cast<float>(cam.width);
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float h = static_cast<float>(cam.height);
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balance = std::min(std::max(balance, 0.0f), 1.0f);
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// Define four key points at the middle of each edge
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std::vector<std ::array<float, 2>> pts = {
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{w * 0.5f, 0.0},
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{w, h * 0.5f},
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{w * 0.5f, h},
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{0.0, h * 0.5f}};
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// Extract intrinsic parameters
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float fx = cam.K[0][0];
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float fy = cam.K[1][1];
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float cx = cam.K[0][2];
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float cy = cam.K[1][2];
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// Undistort the edge points
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for (auto &pt : pts)
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{
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std::array<float, 3> p_normed = {(pt[0] - cx) / fx, (pt[1] - cy) / fy, 1.0};
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undistort_point_fisheye(p_normed, cam.DC);
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pt[0] = p_normed[0];
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pt[1] = p_normed[1];
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}
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// Compute center mass of the undistorted edge points
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float sum_x = 0.0, sum_y = 0.0;
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for (const auto &pt : pts)
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{
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sum_x += pt[0];
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sum_y += pt[1];
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}
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float cn_x = sum_x / pts.size();
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float cn_y = sum_y / pts.size();
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// Convert to identity ratio
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float aspect_ratio = fx / fy;
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cn_y *= aspect_ratio;
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for (auto &pt : pts)
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pt[1] *= aspect_ratio;
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// Find the bounding box of the undistorted points
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float minx = std::numeric_limits<float>::max();
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float miny = std::numeric_limits<float>::max();
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float maxx = -std::numeric_limits<float>::max();
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float maxy = -std::numeric_limits<float>::max();
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for (const auto &pt : pts)
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{
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minx = std::min(minx, pt[0]);
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maxx = std::max(maxx, pt[0]);
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miny = std::min(miny, pt[1]);
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maxy = std::max(maxy, pt[1]);
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}
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// Calculate candidate focal lengths
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float f1 = (w * 0.5) / (cn_x - minx);
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float f2 = (w * 0.5) / (maxx - cn_x);
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float f3 = (h * 0.5 * aspect_ratio) / (cn_y - miny);
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float f4 = (h * 0.5 * aspect_ratio) / (maxy - cn_y);
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float fmin = std::min({f1, f2, f3, f4});
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float fmax = std::max({f1, f2, f3, f4});
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// Blend the candidate focal lengths
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float f_val = balance * fmin + (1.0f - balance) * fmax;
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if (fov_scale > 0.0f)
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f_val /= fov_scale;
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// Compute new intrinsic parameters
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float new_fx = f_val;
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float new_fy = f_val;
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float new_cx = -cn_x * f_val + (w * 0.5);
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float new_cy = -cn_y * f_val + (h * aspect_ratio * 0.5);
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// Restore aspect ratio
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new_fy /= aspect_ratio;
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new_cy /= aspect_ratio;
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// Optionally scale parameters to new new image size
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if (new_size.first > 0 && new_size.second > 0)
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{
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float rx = static_cast<float>(new_size.first) / w;
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float ry = static_cast<float>(new_size.second) / h;
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new_fx *= rx;
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new_fy *= ry;
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new_cx *= rx;
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new_cy *= ry;
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}
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std::array<std::array<float, 3>, 3> newK = {
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{{new_fx, 0.0, new_cx},
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{0.0, new_fy, new_cy},
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{0.0, 0.0, 1.0}}};
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return newK;
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}
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// =================================================================================================
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std::array<std::array<float, 3>, 3> CameraInternal::calc_optimal_camera_matrix_pinhole(
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float alpha, std::pair<int, int> new_size)
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{
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// Following: cv::getOptimalNewCameraMatrix
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// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/calibration_base.cpp#L1565
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bool center_principal_point = false;
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bool use_pix_roi = false;
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float w = static_cast<float>(cam.width);
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float h = static_cast<float>(cam.height);
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alpha = std::min(std::max(alpha, 0.0f), 1.0f);
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if (center_principal_point || use_pix_roi)
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{
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// Not implemented
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exit(1);
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}
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// Define key points
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const size_t N = 9;
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std::vector<std ::array<float, 2>> pts;
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pts.reserve(N * N);
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for (size_t y = 0; y < N; ++y)
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{
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for (size_t x = 0; x < N; ++x)
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{
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pts.push_back({x * (w - 1) / (N - 1), y * (h - 1) / (N - 1)});
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}
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}
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// Extract intrinsic parameters
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float fx = cam.K[0][0];
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float fy = cam.K[1][1];
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float cx = cam.K[0][2];
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float cy = cam.K[1][2];
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// Undistort the key points
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for (auto &pt : pts)
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{
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std::array<float, 3> p_normed = {(pt[0] - cx) / fx, (pt[1] - cy) / fy, 1.0};
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undistort_point_pinhole(p_normed, cam.DC);
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pt[0] = p_normed[0];
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pt[1] = p_normed[1];
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}
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// Get inscribed and circumscribed rectangles in normalized coordinates
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float iX0 = -std::numeric_limits<float>::max();
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float iX1 = std::numeric_limits<float>::max();
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float iY0 = -std::numeric_limits<float>::max();
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float iY1 = std::numeric_limits<float>::max();
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float oX0 = std::numeric_limits<float>::max();
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float oX1 = -std::numeric_limits<float>::max();
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float oY0 = std::numeric_limits<float>::max();
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float oY1 = -std::numeric_limits<float>::max();
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size_t k = 0;
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for (size_t y = 0; y < N; ++y)
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{
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for (size_t x = 0; x < N; ++x)
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{
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auto &pt = pts[k];
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k += 1;
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oX0 = std::min(oX0, pt[0]);
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oX1 = std::max(oX1, pt[0]);
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oY0 = std::min(oY0, pt[1]);
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oY1 = std::max(oY1, pt[1]);
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if (x == 0)
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iX0 = std::max(iX0, pt[0]);
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if (x == N - 1)
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iX1 = std::min(iX1, pt[0]);
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if (y == 0)
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iY0 = std::max(iY0, pt[1]);
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if (y == N - 1)
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iY1 = std::min(iY1, pt[1]);
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}
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}
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float inner_width = iX1 - iX0;
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float inner_height = iY1 - iY0;
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float outer_width = oX1 - oX0;
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float outer_height = oY1 - oY0;
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// Projection mapping inner rectangle to viewport
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float fx0 = (new_size.first - 1) / inner_width;
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float fy0 = (new_size.second - 1) / inner_height;
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float cx0 = -fx0 * iX0;
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float cy0 = -fy0 * iY0;
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// Projection mapping outer rectangle to viewport
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float fx1 = (new_size.first - 1) / outer_width;
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float fy1 = (new_size.second - 1) / outer_height;
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float cx1 = -fx1 * oX0;
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float cy1 = -fy1 * oY0;
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// Interpolate between the two optimal projections
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float new_fx = fx0 * (1 - alpha) + fx1 * alpha;
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float new_fy = fy0 * (1 - alpha) + fy1 * alpha;
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float new_cx = cx0 * (1 - alpha) + cx1 * alpha;
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float new_cy = cy0 * (1 - alpha) + cy1 * alpha;
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std::array<std::array<float, 3>, 3> newK = {
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{{new_fx, 0.0, new_cx},
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{0.0, new_fy, new_cy},
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{0.0, 0.0, 1.0}}};
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return newK;
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}
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// =================================================================================================
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@ -213,7 +563,6 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
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for (size_t i = 0; i < cameras.size(); ++i)
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{
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undistort_poses(i_poses_2d[i], internal_cameras[i]);
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internal_cameras[i].update_projection_matrix();
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}
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elapsed = std::chrono::steady_clock::now() - stime;
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@ -601,84 +950,6 @@ void TriangulatorInternal::print_stats()
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// =================================================================================================
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void undistort_point_pinhole(std::array<float, 3> &p, const std::vector<float> &k)
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{
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// Use distortion coefficients: [k1, k2, p1, p2, k3]
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// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/undistort.dispatch.cpp#L432
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float x0 = p[0];
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float y0 = p[1];
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float x = x0;
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float y = y0;
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// Iteratively refine the estimate for the undistorted point.
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int max_iterations = 5;
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for (int iter = 0; iter < max_iterations; ++iter)
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{
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float r2 = x * x + y * y;
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double icdist = 1.0 / (1 + ((k[4] * r2 + k[1]) * r2 + k[0]) * r2);
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if (icdist < 0)
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{
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x = x0;
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y = y0;
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break;
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}
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float deltaX = 2 * k[2] * x * y + k[3] * (r2 + 2 * x * x);
|
||||
float deltaY = k[2] * (r2 + 2 * y * y) + 2 * k[3] * x * y;
|
||||
x = (x0 - deltaX) * icdist;
|
||||
y = (y0 - deltaY) * icdist;
|
||||
}
|
||||
|
||||
p[0] = x;
|
||||
p[1] = y;
|
||||
}
|
||||
|
||||
void undistort_point_fisheye(std::array<float, 3> &p, const std::vector<float> &k)
|
||||
{
|
||||
// Use distortion coefficients: [k1, k2, k3, k4]
|
||||
// https://github.com/opencv/opencv/blob/4.x/modules/calib3d/src/fisheye.cpp#L429
|
||||
|
||||
float theta_d = std::sqrt(p[0] * p[0] + p[1] * p[1]);
|
||||
float pi_half = std::numbers::pi * 0.5;
|
||||
theta_d = std::min(std::max(-pi_half, theta_d), pi_half);
|
||||
|
||||
if (theta_d < 1e-6)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
float scale = 0.0;
|
||||
float theta = theta_d;
|
||||
|
||||
int max_iterations = 5;
|
||||
for (int iter = 0; iter < max_iterations; ++iter)
|
||||
{
|
||||
float theta2 = theta * theta;
|
||||
float theta4 = theta2 * theta2;
|
||||
float theta6 = theta4 * theta2;
|
||||
float theta8 = theta4 * theta4;
|
||||
|
||||
float k0_theta2 = k[0] * theta2;
|
||||
float k1_theta4 = k[1] * theta4;
|
||||
float k2_theta6 = k[2] * theta6;
|
||||
float k3_theta8 = k[3] * theta8;
|
||||
|
||||
float theta_fix = (theta * (1 + k0_theta2 + k1_theta4 + k2_theta6 + k3_theta8) - theta_d) /
|
||||
(1 + 3 * k0_theta2 + 5 * k1_theta4 + 7 * k2_theta6 + 9 * k3_theta8);
|
||||
theta = theta - theta_fix;
|
||||
|
||||
if (std::fabs(theta_fix) < 1e-6)
|
||||
{
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
scale = std::tan(theta) / theta_d;
|
||||
p[0] *= scale;
|
||||
p[1] *= scale;
|
||||
}
|
||||
|
||||
void TriangulatorInternal::undistort_poses(
|
||||
std::vector<std::vector<std::array<float, 3>>> &poses_2d, CameraInternal &icam)
|
||||
{
|
||||
@ -686,27 +957,25 @@ void TriangulatorInternal::undistort_poses(
|
||||
int height = icam.cam.height;
|
||||
|
||||
// Undistort camera matrix
|
||||
cv::Mat newK;
|
||||
// As with the undistortion, the own implementation avoids some overhead compared to OpenCV
|
||||
std::array<std::array<float, 3>, 3> newK;
|
||||
if (icam.cam.type == "fisheye")
|
||||
{
|
||||
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(
|
||||
icam.K, icam.DC, cv::Size(width, height), cv::Matx33d::eye(),
|
||||
newK, 1.0, cv::Size(width, height), 1.0);
|
||||
newK = icam.calc_optimal_camera_matrix_fisheye(1.0, {width, height});
|
||||
}
|
||||
else
|
||||
{
|
||||
newK = cv::getOptimalNewCameraMatrix(
|
||||
icam.K, icam.DC, cv::Size(width, height), 1, cv::Size(width, height));
|
||||
newK = icam.calc_optimal_camera_matrix_pinhole(1.0, {width, height});
|
||||
}
|
||||
|
||||
float ifx_old = 1.0 / icam.cam.K[0][0];
|
||||
float ify_old = 1.0 / icam.cam.K[1][1];
|
||||
float cx_old = icam.cam.K[0][2];
|
||||
float cy_old = icam.cam.K[1][2];
|
||||
float fx_new = newK.at<float>(0, 0);
|
||||
float fy_new = newK.at<float>(1, 1);
|
||||
float cx_new = newK.at<float>(0, 2);
|
||||
float cy_new = newK.at<float>(1, 2);
|
||||
float fx_new = newK[0][0];
|
||||
float fy_new = newK[1][1];
|
||||
float cx_new = newK[0][2];
|
||||
float cy_new = newK[1][2];
|
||||
|
||||
// Undistort all the points
|
||||
size_t num_persons = poses_2d.size();
|
||||
@ -725,11 +994,11 @@ void TriangulatorInternal::undistort_poses(
|
||||
// additional distortion parameters and identity rotations in this usecase.
|
||||
if (icam.cam.type == "fisheye")
|
||||
{
|
||||
undistort_point_fisheye(poses_2d[i][j], icam.cam.DC);
|
||||
CameraInternal::undistort_point_fisheye(poses_2d[i][j], icam.cam.DC);
|
||||
}
|
||||
else
|
||||
{
|
||||
undistort_point_pinhole(poses_2d[i][j], icam.cam.DC);
|
||||
CameraInternal::undistort_point_pinhole(poses_2d[i][j], icam.cam.DC);
|
||||
}
|
||||
|
||||
// Map the undistorted normalized point to the new image coordinates
|
||||
@ -754,23 +1023,15 @@ void TriangulatorInternal::undistort_poses(
|
||||
}
|
||||
}
|
||||
|
||||
// Update the camera matrix
|
||||
icam.K = newK.clone();
|
||||
for (size_t i = 0; i < 3; ++i)
|
||||
{
|
||||
for (size_t j = 0; j < 3; ++j)
|
||||
{
|
||||
icam.cam.K[i][j] = newK.at<float>(i, j);
|
||||
}
|
||||
}
|
||||
// Update the camera intrinsics
|
||||
icam.cam.K = newK;
|
||||
icam.invK = CameraInternal::invert3x3(newK);
|
||||
if (icam.cam.type == "fisheye")
|
||||
{
|
||||
icam.DC = cv::Mat::zeros(4, 1, CV_32F);
|
||||
icam.cam.DC = {0.0, 0.0, 0.0, 0.0};
|
||||
}
|
||||
else
|
||||
{
|
||||
icam.DC = cv::Mat::zeros(5, 1, CV_32F);
|
||||
icam.cam.DC = {0.0, 0.0, 0.0, 0.0, 0.0};
|
||||
}
|
||||
}
|
||||
@ -1008,62 +1269,6 @@ std::vector<float> TriangulatorInternal::score_projection(
|
||||
|
||||
// =================================================================================================
|
||||
|
||||
/* Compute the inverse using the adjugate method */
|
||||
std::array<std::array<float, 3>, 3> invert3x3(const std::array<std::array<float, 3>, 3> &M)
|
||||
{
|
||||
// See: https://scicomp.stackexchange.com/a/29206
|
||||
|
||||
std::array<std::array<float, 3>, 3> adj = {
|
||||
{{
|
||||
M[1][1] * M[2][2] - M[1][2] * M[2][1],
|
||||
M[0][2] * M[2][1] - M[0][1] * M[2][2],
|
||||
M[0][1] * M[1][2] - M[0][2] * M[1][1],
|
||||
},
|
||||
{
|
||||
M[1][2] * M[2][0] - M[1][0] * M[2][2],
|
||||
M[0][0] * M[2][2] - M[0][2] * M[2][0],
|
||||
M[0][2] * M[1][0] - M[0][0] * M[1][2],
|
||||
},
|
||||
{
|
||||
M[1][0] * M[2][1] - M[1][1] * M[2][0],
|
||||
M[0][1] * M[2][0] - M[0][0] * M[2][1],
|
||||
M[0][0] * M[1][1] - M[0][1] * M[1][0],
|
||||
}}};
|
||||
|
||||
float det = M[0][0] * adj[0][0] + M[0][1] * adj[1][0] + M[0][2] * adj[2][0];
|
||||
if (std::fabs(det) < 1e-6f)
|
||||
{
|
||||
return {{{0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}}};
|
||||
}
|
||||
|
||||
float idet = 1.0f / det;
|
||||
std::array<std::array<float, 3>, 3> inv = {
|
||||
{{
|
||||
adj[0][0] * idet,
|
||||
adj[0][1] * idet,
|
||||
adj[0][2] * idet,
|
||||
},
|
||||
{
|
||||
adj[1][0] * idet,
|
||||
adj[1][1] * idet,
|
||||
adj[1][2] * idet,
|
||||
},
|
||||
{
|
||||
adj[2][0] * idet,
|
||||
adj[2][1] * idet,
|
||||
adj[2][2] * idet,
|
||||
}}};
|
||||
|
||||
return inv;
|
||||
}
|
||||
|
||||
std::array<std::array<float, 3>, 3> transpose3x3(const std::array<std::array<float, 3>, 3> &M)
|
||||
{
|
||||
return {{{M[0][0], M[1][0], M[2][0]},
|
||||
{M[0][1], M[1][1], M[2][1]},
|
||||
{M[0][2], M[1][2], M[2][2]}}};
|
||||
}
|
||||
|
||||
float dot(const std::array<float, 3> &a, const std::array<float, 3> &b)
|
||||
{
|
||||
return a[0] * b[0] + a[1] * b[1] + a[2] * b[2];
|
||||
@ -1102,40 +1307,30 @@ std::array<float, 3> mat_mul_vec(
|
||||
return res;
|
||||
}
|
||||
|
||||
/* Compute camera center and corresponding ray direction */
|
||||
std::tuple<std::array<float, 3>, std::array<float, 3>> calc_center_and_ray(
|
||||
const CameraInternal &icam,
|
||||
const std::array<float, 2> &pt)
|
||||
std::array<float, 3> calc_ray_dir(const CameraInternal &icam, const std::array<float, 2> &pt)
|
||||
{
|
||||
// Compute Rᵀ and t
|
||||
auto R_transpose = transpose3x3(icam.cam.R);
|
||||
std::array<float, 3> t = {icam.cam.T[0][0], icam.cam.T[1][0], icam.cam.T[2][0]};
|
||||
t = mat_mul_vec(icam.cam.R, multiply(t, -1.0f));
|
||||
// Compute normalized ray direction from the point
|
||||
std::array<float, 3> uv1 = {pt[0], pt[1], 1.0};
|
||||
auto d = mat_mul_vec(icam.invR, mat_mul_vec(icam.invK, uv1));
|
||||
auto ray_dir = normalize(d);
|
||||
|
||||
// Camera center: C = -Rᵀ * t
|
||||
auto C = multiply(mat_mul_vec(R_transpose, t), -1.0f);
|
||||
|
||||
// Compute ray direction:
|
||||
std::array<float, 3> uv1 = {pt[0], pt[1], 1.0f};
|
||||
auto K_inv = invert3x3(icam.cam.K);
|
||||
auto d = mat_mul_vec(R_transpose, mat_mul_vec(K_inv, uv1));
|
||||
auto rayDir = normalize(d);
|
||||
|
||||
return std::make_tuple(C, rayDir);
|
||||
return ray_dir;
|
||||
}
|
||||
|
||||
/* Triangulate two points by computing their two rays and the midpoint of their closest approach */
|
||||
std::array<float, 3> triangulate_midpoint(
|
||||
const CameraInternal &icam1,
|
||||
const CameraInternal &icam2,
|
||||
const std::array<float, 2> &pt1,
|
||||
const std::array<float, 2> &pt2)
|
||||
{
|
||||
// Triangulate two points by computing their two rays and the midpoint of their closest approach
|
||||
// See: https://en.wikipedia.org/wiki/Skew_lines#Nearest_points
|
||||
|
||||
// Obtain the camera centers and ray directions for both views
|
||||
auto [p1, d1] = calc_center_and_ray(icam1, pt1);
|
||||
auto [p2, d2] = calc_center_and_ray(icam2, pt2);
|
||||
std::array<float, 3> p1 = icam1.center;
|
||||
std::array<float, 3> p2 = icam2.center;
|
||||
std::array<float, 3> d1 = calc_ray_dir(icam1, pt1);
|
||||
std::array<float, 3> d2 = calc_ray_dir(icam2, pt2);
|
||||
|
||||
// Compute the perpendicular plane vectors
|
||||
std::array<float, 3> n = cross(d1, d2);
|
||||
|
||||
Reference in New Issue
Block a user