diff options
Diffstat (limited to 'intern/libmv/libmv/simple_pipeline/keyframe_selection.cc')
| -rw-r--r-- | intern/libmv/libmv/simple_pipeline/keyframe_selection.cc | 107 |
1 files changed, 45 insertions, 62 deletions
diff --git a/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc b/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc index 241b5600505..5526d730651 100644 --- a/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc +++ b/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc @@ -20,20 +20,20 @@ #include "libmv/simple_pipeline/keyframe_selection.h" -#include "libmv/numeric/numeric.h" #include "ceres/ceres.h" #include "libmv/logging/logging.h" -#include "libmv/multiview/homography.h" #include "libmv/multiview/fundamental.h" -#include "libmv/simple_pipeline/intersect.h" +#include "libmv/multiview/homography.h" +#include "libmv/numeric/numeric.h" #include "libmv/simple_pipeline/bundle.h" +#include "libmv/simple_pipeline/intersect.h" #include <Eigen/Eigenvalues> namespace libmv { namespace { -Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics &intrinsics) { +Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics& intrinsics) { Mat3 T = Mat3::Identity(), S = Mat3::Identity(); T(0, 2) = -intrinsics.principal_point_x(); @@ -56,7 +56,7 @@ Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics &intrinsics) { // (k = 7 for a fundamental matrix or 8 for a homography) // r is the dimension of the data // (r = 4 for 2D correspondences between two frames) -double GRIC(const Vec &e, int d, int k, int r) { +double GRIC(const Vec& e, int d, int k, int r) { int n = e.rows(); double lambda1 = log(static_cast<double>(r)); double lambda2 = log(static_cast<double>(r * n)); @@ -89,7 +89,7 @@ double GRIC(const Vec &e, int d, int k, int r) { // // TODO(keir): Consider moving this into the numeric code, since this is not // related to keyframe selection. -Mat PseudoInverseWithClampedEigenvalues(const Mat &matrix, +Mat PseudoInverseWithClampedEigenvalues(const Mat& matrix, int num_eigenvalues_to_clamp) { Eigen::EigenSolver<Mat> eigen_solver(matrix); Mat D = eigen_solver.pseudoEigenvalueMatrix(); @@ -112,27 +112,24 @@ Mat PseudoInverseWithClampedEigenvalues(const Mat &matrix, return V * D * V.inverse(); } -void FilterZeroWeightMarkersFromTracks(const Tracks &tracks, - Tracks *filtered_tracks) { +void FilterZeroWeightMarkersFromTracks(const Tracks& tracks, + Tracks* filtered_tracks) { vector<Marker> all_markers = tracks.AllMarkers(); for (int i = 0; i < all_markers.size(); ++i) { - Marker &marker = all_markers[i]; + Marker& marker = all_markers[i]; if (marker.weight != 0.0) { - filtered_tracks->Insert(marker.image, - marker.track, - marker.x, - marker.y, - marker.weight); + filtered_tracks->Insert( + marker.image, marker.track, marker.x, marker.y, marker.weight); } } } } // namespace -void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, - const CameraIntrinsics &intrinsics, - vector<int> &keyframes) { +void SelectKeyframesBasedOnGRICAndVariance(const Tracks& _tracks, + const CameraIntrinsics& intrinsics, + vector<int>& keyframes) { // Mirza Tahir Ahmed, Matthew N. Dailey // Robust key frame extraction for 3D reconstruction from video streams // @@ -172,23 +169,21 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, candidate_image <= max_image; candidate_image++) { // Conjunction of all markers from both keyframes - vector<Marker> all_markers = - filtered_tracks.MarkersInBothImages(current_keyframe, - candidate_image); + vector<Marker> all_markers = filtered_tracks.MarkersInBothImages( + current_keyframe, candidate_image); // Match keypoints between frames current_keyframe and candidate_image vector<Marker> tracked_markers = - filtered_tracks.MarkersForTracksInBothImages(current_keyframe, - candidate_image); + filtered_tracks.MarkersForTracksInBothImages(current_keyframe, + candidate_image); // Correspondences in normalized space Mat x1, x2; CoordinatesForMarkersInImage(tracked_markers, current_keyframe, &x1); CoordinatesForMarkersInImage(tracked_markers, candidate_image, &x2); - LG << "Found " << x1.cols() - << " correspondences between " << current_keyframe - << " and " << candidate_image; + LG << "Found " << x1.cols() << " correspondences between " + << current_keyframe << " and " << candidate_image; // Not enough points to construct fundamental matrix if (x1.cols() < 8 || x2.cols() < 8) @@ -199,9 +194,8 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, int Tf = all_markers.size(); double Rc = static_cast<double>(Tc) / Tf; - LG << "Correspondence between " << current_keyframe - << " and " << candidate_image - << ": " << Rc; + LG << "Correspondence between " << current_keyframe << " and " + << candidate_image << ": " << Rc; if (Rc < Tmin || Rc > Tmax) continue; @@ -210,19 +204,15 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, // Estimate homography using default options. EstimateHomographyOptions estimate_homography_options; - EstimateHomography2DFromCorrespondences(x1, - x2, - estimate_homography_options, - &H); + EstimateHomography2DFromCorrespondences( + x1, x2, estimate_homography_options, &H); // Convert homography to original pixel space. H = N_inverse * H * N; EstimateFundamentalOptions estimate_fundamental_options; - EstimateFundamentalFromCorrespondences(x1, - x2, - estimate_fundamental_options, - &F); + EstimateFundamentalFromCorrespondences( + x1, x2, estimate_fundamental_options, &F); // Convert fundamental to original pixel space. F = N_inverse * F * N; @@ -238,11 +228,11 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, for (int i = 0; i < x1.cols(); i++) { Vec2 current_x1, current_x2; - intrinsics.NormalizedToImageSpace(x1(0, i), x1(1, i), - ¤t_x1(0), ¤t_x1(1)); + intrinsics.NormalizedToImageSpace( + x1(0, i), x1(1, i), ¤t_x1(0), ¤t_x1(1)); - intrinsics.NormalizedToImageSpace(x2(0, i), x2(1, i), - ¤t_x2(0), ¤t_x2(1)); + intrinsics.NormalizedToImageSpace( + x2(0, i), x2(1, i), ¤t_x2(0), ¤t_x2(1)); H_e(i) = SymmetricGeometricDistance(H, current_x1, current_x2); F_e(i) = SymmetricEpipolarDistance(F, current_x1, current_x2); @@ -255,10 +245,8 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, double GRIC_H = GRIC(H_e, 2, 8, 4); double GRIC_F = GRIC(F_e, 3, 7, 4); - LG << "GRIC values for frames " << current_keyframe - << " and " << candidate_image - << ", H-GRIC: " << GRIC_H - << ", F-GRIC: " << GRIC_F; + LG << "GRIC values for frames " << current_keyframe << " and " + << candidate_image << ", H-GRIC: " << GRIC_H << ", F-GRIC: " << GRIC_F; if (GRIC_H <= GRIC_F) continue; @@ -295,23 +283,19 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, Vec3 t; Mat3 K = Mat3::Identity(); - if (!MotionFromEssentialAndCorrespondence(E, - K, x1.col(0), - K, x2.col(0), - &R, &t)) { + if (!MotionFromEssentialAndCorrespondence( + E, K, x1.col(0), K, x2.col(0), &R, &t)) { LG << "Failed to compute R and t from E and K"; continue; } - LG << "Camera transform between frames " << current_keyframe - << " and " << candidate_image - << ":\nR:\n" << R - << "\nt:" << t.transpose(); + LG << "Camera transform between frames " << current_keyframe << " and " + << candidate_image << ":\nR:\n" + << R << "\nt:" << t.transpose(); // First camera is identity, second one is relative to it - reconstruction.InsertCamera(current_keyframe, - Mat3::Identity(), - Vec3::Zero()); + reconstruction.InsertCamera( + current_keyframe, Mat3::Identity(), Vec3::Zero()); reconstruction.InsertCamera(candidate_image, R, t); // Reconstruct 3D points @@ -349,7 +333,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, } double success_intersects_factor = - (double) intersects_success / intersects_total; + (double)intersects_success / intersects_total; if (success_intersects_factor < success_intersects_factor_best) { LG << "Skip keyframe candidate because of " @@ -372,7 +356,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, &empty_intrinsics, &evaluation); - Mat &jacobian = evaluation.jacobian; + Mat& jacobian = evaluation.jacobian; Mat JT_J = jacobian.transpose() * jacobian; // There are 7 degrees of freedom, so clamp them out. @@ -380,10 +364,10 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, Mat temp_derived = JT_J * JT_J_inv * JT_J; bool is_inversed = (temp_derived - JT_J).cwiseAbs2().sum() < - 1e-4 * std::min(temp_derived.cwiseAbs2().sum(), - JT_J.cwiseAbs2().sum()); + 1e-4 * std::min(temp_derived.cwiseAbs2().sum(), + JT_J.cwiseAbs2().sum()); - LG << "Check on inversed: " << (is_inversed ? "true" : "false" ) + LG << "Check on inversed: " << (is_inversed ? "true" : "false") << ", det(JT_J): " << JT_J.determinant(); if (!is_inversed) { @@ -400,8 +384,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, double Sc = static_cast<double>(I + A) / Square(3 * I) * Sigma_P.trace(); - LG << "Expected estimation error between " - << current_keyframe << " and " + LG << "Expected estimation error between " << current_keyframe << " and " << candidate_image << ": " << Sc; // Pairing with a lower Sc indicates a better choice |