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in solvePnPRansac call the solvePnP in the end with all the inliers to get more precise estimate
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5c352c9146
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@ -20,7 +20,7 @@ typedef perf::TestBaseWithParam<int> PointsNum;
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PERF_TEST_P(PointsNum_Algo, solvePnP,
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testing::Combine(
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testing::Values(5, 3*9, 7*13), //TODO: find why results on 4 points are too unstable
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testing::Values((int)SOLVEPNP_ITERATIVE, (int)SOLVEPNP_EPNP)
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testing::Values((int)SOLVEPNP_ITERATIVE, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_UPNP, (int)SOLVEPNP_DLS)
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)
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)
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{
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@ -64,13 +64,15 @@ PERF_TEST_P(PointsNum_Algo, solvePnP,
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PERF_TEST_P(PointsNum_Algo, solvePnPSmallPoints,
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testing::Combine(
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testing::Values(4),
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testing::Values((int)SOLVEPNP_P3P, (int)SOLVEPNP_DLS, (int)SOLVEPNP_UPNP)
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testing::Values(5),
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testing::Values((int)SOLVEPNP_P3P, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_DLS, (int)SOLVEPNP_UPNP)
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)
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)
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{
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int pointsNum = get<0>(GetParam());
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pnpAlgo algo = get<1>(GetParam());
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if( algo == SOLVEPNP_P3P )
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pointsNum = 4;
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vector<Point2f> points2d(pointsNum);
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vector<Point3f> points3d(pointsNum);
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@ -2,7 +2,10 @@
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#include "precomp.hpp"
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#include "epnp.h"
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epnp::epnp(const cv::Mat& cameraMatrix, const cv::Mat& opoints, const cv::Mat& ipoints)
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namespace cv
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{
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epnp::epnp(const Mat& cameraMatrix, const Mat& opoints, const Mat& ipoints)
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{
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if (cameraMatrix.depth() == CV_32F)
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init_camera_parameters<float>(cameraMatrix);
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@ -17,14 +20,14 @@ epnp::epnp(const cv::Mat& cameraMatrix, const cv::Mat& opoints, const cv::Mat& i
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if (opoints.depth() == ipoints.depth())
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{
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if (opoints.depth() == CV_32F)
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init_points<cv::Point3f,cv::Point2f>(opoints, ipoints);
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init_points<Point3f,Point2f>(opoints, ipoints);
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else
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init_points<cv::Point3d,cv::Point2d>(opoints, ipoints);
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init_points<Point3d,Point2d>(opoints, ipoints);
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}
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else if (opoints.depth() == CV_32F)
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init_points<cv::Point3f,cv::Point2d>(opoints, ipoints);
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init_points<Point3f,Point2d>(opoints, ipoints);
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else
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init_points<cv::Point3d,cv::Point2f>(opoints, ipoints);
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init_points<Point3d,Point2f>(opoints, ipoints);
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alphas.resize(4 * number_of_correspondences);
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pcs.resize(3 * number_of_correspondences);
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@ -144,7 +147,7 @@ void epnp::compute_pcs(void)
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}
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}
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void epnp::compute_pose(cv::Mat& R, cv::Mat& t)
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void epnp::compute_pose(Mat& R, Mat& t)
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{
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choose_control_points();
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compute_barycentric_coordinates();
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@ -189,8 +192,8 @@ void epnp::compute_pose(cv::Mat& R, cv::Mat& t)
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if (rep_errors[2] < rep_errors[1]) N = 2;
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if (rep_errors[3] < rep_errors[N]) N = 3;
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cv::Mat(3, 1, CV_64F, ts[N]).copyTo(t);
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cv::Mat(3, 3, CV_64F, Rs[N]).copyTo(R);
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Mat(3, 1, CV_64F, ts[N]).copyTo(t);
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Mat(3, 3, CV_64F, Rs[N]).copyTo(R);
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}
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void epnp::copy_R_and_t(const double R_src[3][3], const double t_src[3],
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@ -621,3 +624,5 @@ void epnp::qr_solve(CvMat * A, CvMat * b, CvMat * X)
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pX[i] = (pb[i] - sum) / A2[i];
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}
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}
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}
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@ -4,6 +4,9 @@
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#include "precomp.hpp"
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#include "opencv2/core/core_c.h"
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namespace cv
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{
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class epnp {
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public:
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epnp(const cv::Mat& cameraMatrix, const cv::Mat& opoints, const cv::Mat& ipoints);
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@ -78,4 +81,6 @@ class epnp {
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double * A1, * A2;
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};
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}
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#endif
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@ -69,20 +69,6 @@ static bool haveCollinearPoints( const Mat& m, int count )
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}
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template<typename T> int compressPoints( T* ptr, const uchar* mask, int mstep, int count )
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{
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int i, j;
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for( i = j = 0; i < count; i++ )
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if( mask[i*mstep] )
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{
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if( i > j )
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ptr[j] = ptr[i];
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j++;
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}
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return j;
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}
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class HomographyEstimatorCallback : public PointSetRegistrator::Callback
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{
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public:
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@ -322,8 +308,8 @@ cv::Mat cv::findHomography( InputArray _points1, InputArray _points2,
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if( result && npoints > 4 )
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{
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compressPoints( src.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );
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npoints = compressPoints( dst.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );
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compressElems( src.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );
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npoints = compressElems( dst.ptr<Point2f>(), tempMask.ptr<uchar>(), 1, npoints );
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if( npoints > 0 )
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{
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Mat src1 = src.rowRange(0, npoints);
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@ -102,6 +102,19 @@ CV_EXPORTS Ptr<PointSetRegistrator> createRANSACPointSetRegistrator(const Ptr<Po
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CV_EXPORTS Ptr<PointSetRegistrator> createLMeDSPointSetRegistrator(const Ptr<PointSetRegistrator::Callback>& cb,
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int modelPoints, double confidence=0.99, int maxIters=1000 );
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template<typename T> inline int compressElems( T* ptr, const uchar* mask, int mstep, int count )
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{
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int i, j;
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for( i = j = 0; i < count; i++ )
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if( mask[i*mstep] )
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{
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if( i > j )
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ptr[j] = ptr[i];
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j++;
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}
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return j;
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}
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}
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#endif
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@ -48,11 +48,13 @@
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#include "opencv2/calib3d/calib3d_c.h"
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#include <iostream>
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using namespace cv;
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bool cv::solvePnP( InputArray _opoints, InputArray _ipoints,
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InputArray _cameraMatrix, InputArray _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
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namespace cv
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{
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bool solvePnP( InputArray _opoints, InputArray _ipoints,
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InputArray _cameraMatrix, InputArray _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
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{
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Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
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int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
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@ -63,26 +65,26 @@ bool cv::solvePnP( InputArray _opoints, InputArray _ipoints,
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if (flags == SOLVEPNP_EPNP || flags == SOLVEPNP_DLS || flags == SOLVEPNP_UPNP)
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{
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cv::Mat undistortedPoints;
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cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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epnp PnP(cameraMatrix, opoints, undistortedPoints);
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cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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PnP.compute_pose(R, tvec);
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cv::Rodrigues(R, rvec);
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Rodrigues(R, rvec);
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return true;
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}
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else if (flags == SOLVEPNP_P3P)
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{
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CV_Assert( npoints == 4);
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cv::Mat undistortedPoints;
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cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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p3p P3Psolver(cameraMatrix);
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cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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bool result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
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if (result)
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cv::Rodrigues(R, rvec);
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Rodrigues(R, rvec);
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return result;
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}
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else if (flags == SOLVEPNP_ITERATIVE)
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@ -97,24 +99,24 @@ bool cv::solvePnP( InputArray _opoints, InputArray _ipoints,
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}
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/*else if (flags == SOLVEPNP_DLS)
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{
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cv::Mat undistortedPoints;
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cv::undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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Mat undistortedPoints;
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undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
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dls PnP(opoints, undistortedPoints);
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cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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bool result = PnP.compute_pose(R, tvec);
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if (result)
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cv::Rodrigues(R, rvec);
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Rodrigues(R, rvec);
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return result;
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}
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else if (flags == SOLVEPNP_UPNP)
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{
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upnp PnP(cameraMatrix, opoints, ipoints);
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cv::Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
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double f = PnP.compute_pose(R, tvec);
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cv::Rodrigues(R, rvec);
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Rodrigues(R, rvec);
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if(cameraMatrix.type() == CV_32F)
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cameraMatrix.at<float>(0,0) = cameraMatrix.at<float>(1,1) = (float)f;
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else
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@ -131,7 +133,7 @@ class PnPRansacCallback : public PointSetRegistrator::Callback
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public:
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PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=cv::SOLVEPNP_ITERATIVE,
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PnPRansacCallback(Mat _cameraMatrix=Mat(3,3,CV_64F), Mat _distCoeffs=Mat(4,1,CV_64F), int _flags=SOLVEPNP_ITERATIVE,
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bool _useExtrinsicGuess=false, Mat _rvec=Mat(), Mat _tvec=Mat() )
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: cameraMatrix(_cameraMatrix), distCoeffs(_distCoeffs), flags(_flags), useExtrinsicGuess(_useExtrinsicGuess),
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rvec(_rvec), tvec(_tvec) {}
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@ -142,12 +144,11 @@ public:
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{
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Mat opoints = _m1.getMat(), ipoints = _m2.getMat();
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bool correspondence = cv::solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
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bool correspondence = solvePnP( _m1, _m2, cameraMatrix, distCoeffs,
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rvec, tvec, useExtrinsicGuess, flags );
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Mat _local_model;
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cv::hconcat(rvec, tvec, _local_model);
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hconcat(rvec, tvec, _local_model);
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_local_model.copyTo(_model);
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return correspondence;
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@ -166,7 +167,7 @@ public:
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Mat projpoints(count, 2, CV_32FC1);
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cv::projectPoints(opoints, _rvec, _tvec, cameraMatrix, distCoeffs, projpoints);
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projectPoints(opoints, _rvec, _tvec, cameraMatrix, distCoeffs, projpoints);
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const Point2f* ipoints_ptr = ipoints.ptr<Point2f>();
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const Point2f* projpoints_ptr = projpoints.ptr<Point2f>();
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@ -175,7 +176,7 @@ public:
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float* err = _err.getMat().ptr<float>();
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for ( i = 0; i < count; ++i)
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err[i] = (float)cv::norm( ipoints_ptr[i] - projpoints_ptr[i] );
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err[i] = (float)norm( ipoints_ptr[i] - projpoints_ptr[i] );
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}
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@ -188,7 +189,7 @@ public:
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Mat tvec;
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};
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bool cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
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bool solvePnPRansac(InputArray _opoints, InputArray _ipoints,
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InputArray _cameraMatrix, InputArray _distCoeffs,
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OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess,
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int iterationsCount, float reprojectionError, double confidence,
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@ -214,23 +215,45 @@ bool cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
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Mat tvec = useExtrinsicGuess ? _tvec.getMat() : Mat(3, 1, CV_64FC1);
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Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
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Ptr<PointSetRegistrator::Callback> cb; // pointer to callback
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cb = makePtr<PnPRansacCallback>( cameraMatrix, distCoeffs, flags, useExtrinsicGuess, rvec, tvec);
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int model_points = 5;
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int ransac_kernel_method = SOLVEPNP_EPNP;
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int model_points = 4; // minimum of number of model points
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if( flags == cv::SOLVEPNP_ITERATIVE ) model_points = 6;
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else if( flags == cv::SOLVEPNP_UPNP ) model_points = 6;
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else if( flags == cv::SOLVEPNP_EPNP ) model_points = 5;
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if( npoints == 4 )
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{
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model_points = 4;
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ransac_kernel_method = SOLVEPNP_P3P;
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}
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Ptr<PointSetRegistrator::Callback> cb; // pointer to callback
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cb = makePtr<PnPRansacCallback>( cameraMatrix, distCoeffs, ransac_kernel_method, useExtrinsicGuess, rvec, tvec);
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double param1 = reprojectionError; // reprojection error
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double param2 = confidence; // confidence
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int param3 = iterationsCount; // number maximum iterations
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cv::Mat _local_model(3, 2, CV_64FC1);
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cv::Mat _mask_local_inliers(1, opoints.rows, CV_8UC1);
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Mat _local_model(3, 2, CV_64FC1);
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Mat _mask_local_inliers(1, opoints.rows, CV_8UC1);
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// call Ransac
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int result = createRANSACPointSetRegistrator(cb, model_points, param1, param2, param3)->run(opoints, ipoints, _local_model, _mask_local_inliers);
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int result = createRANSACPointSetRegistrator(cb, model_points,
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param1, param2, param3)->run(opoints, ipoints, _local_model, _mask_local_inliers);
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if( result > 0 )
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{
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vector<Point3d> opoints_inliers;
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vector<Point2d> ipoints_inliers;
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opoints.convertTo(opoints_inliers, CV_64F);
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ipoints.convertTo(ipoints_inliers, CV_64F);
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const uchar* mask = _mask_local_inliers.ptr<uchar>();
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int npoints1 = compressElems(&opoints_inliers[0], mask, 1, npoints);
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compressElems(&ipoints_inliers[0], mask, 1, npoints);
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opoints_inliers.resize(npoints1);
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ipoints_inliers.resize(npoints1);
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result = solvePnP(opoints_inliers, ipoints_inliers, cameraMatrix,
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distCoeffs, rvec, tvec, false, flags == SOLVEPNP_P3P ? SOLVEPNP_EPNP : flags) ? 1 : -1;
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}
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if( result <= 0 || _local_model.rows <= 0)
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{
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@ -260,3 +283,5 @@ bool cv::solvePnPRansac(InputArray _opoints, InputArray _ipoints,
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}
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return true;
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}
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}
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