bool process_sfm(IFeatureDetect *fdetect, IPoseEstimation *poseestim, ITriangulation *triang,
Camera const &cam,
Frame *frame_last, Frame *frame_now, std::vector<Frame *> const &frames,
PointCloud &global_points, SfMTimes ×,
bool initial_pose_estimated, bool export_kp, bool show_matches, bool show_points)
{
double const DISTANCE_THRESHOLD = 10;
StopWatch fdsw;
fdetect->findFeatures(frame_now);
ViewCombination view = fdetect->matchFrames(frame_last, frame_now);
if (export_kp) {
export_keypoints(view);
}
if (show_matches) {
test_show_features_colored(view, view.getMatchesSize(), true);
}
double average_distance = 0.0;
for (size_t i = 0; i < view.getMatchesSize(); i++) {
double distance = ITriangulation::norm(view.getMatchingPointLeft(i),
view.getMatchingPointRight(i));
average_distance += distance;
}
average_distance /= view.getMatchesSize();
fdsw.stop();
std::cout << "average_distance between " << view.getMatchesSize()
<< " matches: " << average_distance << std::endl;
if (average_distance < DISTANCE_THRESHOLD) {
std::cerr << "camera has not moved" << std::endl;
return false;
}
StopWatch pesw;
if (!initial_pose_estimated) {
std::cout << "Estimating initial pose" << std::endl;
if (!initial_pose_estimation(cam, view, poseestim, show_points)) {
std::cerr << "Pose estimation failed" << std::endl;
return false;
}
} else {
std::vector<cv::Point2f> points_2d;
std::vector<cv::Point3f> points_3d;
std::cout << "finding 2D 3D correspondences" << std::endl;
if (!find_2D_3D_correspndences(frame_now, frames, global_points,
fdetect, points_2d, points_3d)) {
std::cerr << "could not find enough correspondences" << std::endl;
return false;
}
std::cout << "Starting PnP" << std::endl;
if (!poseestim->estimatePose(cam, *frame_now, points_3d, points_2d)) {
std::cerr << "PnP failed" << std::endl;
return false;
}
}
pesw.stop();
std::cout << "Starting triangulation of " << view.getMatchesSize() << " keypoints" << std::endl;
StopWatch trsw;
if (!triang->triangulate(cam, view, global_points)) {
std::cerr << "Triangulation failed" << std::endl;
return false;
}
trsw.stop();
/*
OpticalFlowFeatures of;
std::cout << "starting of" << std::endl;
ViewCombination vof = of.matchFrames(frame_last, frame_now);
std::cout << "matches: " << vof.getMatchesSize() << std::endl
<< "kp left: " << frame_last->getKeypointsSize() << std::endl
<< "kp right: " << frame_now->getKeypointsSize() << std::endl;
std::cout << "starting triangulating of" << std::endl;
triang->triangulate(cam, vof,
view.getImageLeft()->getProjectionMatrix(),
view.getImageRight()->getProjectionMatrix(),
global_points);
//of_pts.RunVisualization();
*/
/*
OpticalFlowFeatures of;
std::cout << "starting of" << std::endl;
Frame f1(img_last);
Frame f2(img_now);
ViewCombination vof = of.matchFrames(&f1, &f2);
triang->triangulate(cam, vof,
frame_last->getProjectionMatrix(),
frame_now->getProjectionMatrix(),
global_points);
*/
if (show_points) {
global_points.RunVisualization("Global points in sfm loop");
}
times.feature_detection = fdsw.getDurationMs();
times.pose_estimation = pesw.getDurationMs();
times.triangulation = trsw.getDurationMs();
return true;
}
bool initial_pose_estimation(Camera const &cam, ViewCombination &view, IPoseEstimation *poseestim,
bool show_points, bool debug = false)
{
cv::Mat P_0, P_1;
PointCloud pts;
if (!poseestim->estimatePose(cam, view, P_0, P_1, pts)) {
return false;
}
if (debug) {
std::cout << "Initial Pose estimation successful" << std::endl;
std::cout << "P_0" << std::endl << P_0 << std::endl;
std::cout << "P_1" << std::endl << P_1 << std::endl;
std::cout << "Triangulated " << pts.size() << " 3d points" << std::endl;
}
if (show_points) {
pts.RunVisualization("Initial pose estimation");
}
std::vector<std::pair<size_t, double>> minimalErrors;
for (size_t i = 0; i < pts.size(); i++) {
minimalErrors.emplace_back(i, pts.getError(i));
}
std::sort(minimalErrors.begin(), minimalErrors.end(),
[](std::pair<size_t, double> const &lhs, std::pair<size_t, double> const &rhs)
{
return lhs.second < rhs.second;
});
std::vector<cv::Point2f> img_points_left;
std::vector<cv::Point2f> img_points_right;
std::vector<cv::Point3f> points_3d;
for (size_t i = 0;
(i < minimalErrors.size()) && (minimalErrors[i].second <= 50.0);
i++) {
size_t idx = minimalErrors[i].first;
if (pts.getPoint(idx)(3) <= 0) continue;
img_points_left.emplace_back(view.getMatchingPointLeft(idx));
img_points_right.emplace_back(view.getMatchingPointRight(idx));
cv::Vec4d const &pt = pts.getPoint(idx);
points_3d.emplace_back(pt(0), pt(1), pt(2));
}
if (debug) {
std::cout << "found " << points_3d.size() << " points elegible for PnP" << std::endl;
}
if (points_3d.size() <= 6) {
return false;
}
try {
if (debug) {
std::cout << "PnP of left view" << std::endl;
}
poseestim->estimatePose(cam, *view.getImageLeft(), points_3d, img_points_left);
if (debug) {
std::cout << "PnP of right view" << std::endl;
}
poseestim->estimatePose(cam, *view.getImageRight(), points_3d, img_points_right);
} catch (std::exception e) {
std::cerr << "PnP after initial pose estimation failed: " << e.what();
return false;
}
return true;
}
