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Camera tracking: switch euclidean intersection code to use Ceres

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Would not expect any significant changes in solver behavior, but
it could be more accurate in some cases.

Switching projective intersection to ceres is marked as a TODO
for now.
This commit is contained in:
Sergey Sharybin 2013-02-26 11:46:27 +00:00
parent 87f1326108
commit 05a5cbbda2
1 changed files with 53 additions and 27 deletions
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78
extern/libmv/libmv/simple_pipeline/intersect.cc vendored
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@ -18,6 +18,8 @@
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
#include "libmv/simple_pipeline/intersect.h"
#include "libmv/base/vector.h"
#include "libmv/logging/logging.h"
#include "libmv/multiview/projection.h"
@ -26,39 +28,41 @@
#include "libmv/multiview/projection.h"
#include "libmv/numeric/numeric.h"
#include "libmv/numeric/levenberg_marquardt.h"
#include "libmv/simple_pipeline/intersect.h"
#include "libmv/simple_pipeline/reconstruction.h"
#include "libmv/simple_pipeline/tracks.h"
#include "ceres/ceres.h"
namespace libmv {
namespace {
struct EuclideanIntersectCostFunction {
class EuclideanIntersectCostFunctor {
public:
typedef Vec FMatrixType;
typedef Vec3 XMatrixType;
EuclideanIntersectCostFunctor(const Marker &marker,
const EuclideanCamera &camera)
: marker_(marker), camera_(camera) {}
EuclideanIntersectCostFunction(const vector<Marker> &markers,
const EuclideanReconstruction &reconstruction)
: markers(markers),
reconstruction(reconstruction) {}
template<typename T>
bool operator()(const T *X, T *residuals) const {
typedef Eigen::Matrix<T, 3, 3> Mat3;
typedef Eigen::Matrix<T, 3, 1> Vec3;
Vec operator()(const Vec3 &X) const {
Vec residuals(2 * markers.size());
residuals.setZero();
for (int i = 0; i < markers.size(); ++i) {
const EuclideanCamera &camera =
*reconstruction.CameraForImage(markers[i].image);
Vec3 projected = camera.R * X + camera.t;
Vec3 x(X);
Mat3 R(camera_.R.cast<T>());
Vec3 t(camera_.t.cast<T>());
Vec3 projected = R * x + t;
projected /= projected(2);
residuals[2*i + 0] = projected(0) - markers[i].x;
residuals[2*i + 1] = projected(1) - markers[i].y;
residuals[0] = projected(0) - T(marker_.x);
residuals[1] = projected(1) - T(marker_.y);
return true;
}
return residuals;
}
const vector<Marker> &markers;
const EuclideanReconstruction &reconstruction;
const Marker &marker_;
const EuclideanCamera &camera_;
};
} // namespace
@ -95,13 +99,35 @@ bool EuclideanIntersect(const vector<Marker> &markers,
Xp /= Xp(3);
Vec3 X = Xp.head<3>();
typedef LevenbergMarquardt<EuclideanIntersectCostFunction> Solver;
ceres::Problem problem;
EuclideanIntersectCostFunction triangulate_cost(markers, *reconstruction);
Solver::SolverParameters params;
Solver solver(triangulate_cost);
for (int i = 0; i < markers.size(); ++i) {
const Marker &marker = markers[i];
const EuclideanCamera &camera =
*reconstruction->CameraForImage(marker.image);
Solver::Results results = solver.minimize(params, &X);
problem.AddResidualBlock(
new ceres::AutoDiffCostFunction<
EuclideanIntersectCostFunctor,
2, /* num_residuals */
3>(new EuclideanIntersectCostFunctor(marker, camera)),
NULL,
&X(0));
}
// Configure the solve.
ceres::Solver::Options solver_options;
solver_options.linear_solver_type = ceres::DENSE_NORMAL_CHOLESKY;
solver_options.max_num_iterations = 50;
solver_options.update_state_every_iteration = true;
solver_options.parameter_tolerance = 1e-16;
solver_options.function_tolerance = 1e-16;
// Run the solve.
ceres::Solver::Summary summary;
ceres::Solve(solver_options, &problem, &summary);
VLOG(1) << "Summary:\n" << summary.FullReport();
// Try projecting the point; make sure it's in front of everyone.
for (int i = 0; i < cameras.size(); ++i) {