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Added BA refinement flags into stitching_detailed

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This commit is contained in:
Alexey Spizhevoy
2011-09-22 08:58:48 +00:00
parent 0ad1d0afac
commit 39533a0b1b
4 changed files with 125 additions and 39 deletions
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24
modules/stitching/include/opencv2/stitching/detail/motion_estimators.hpp
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@@ -83,6 +83,13 @@ private:
class CV_EXPORTS BundleAdjusterBase : public Estimator
{
public:
const Mat refinementMask() const { return refinement_mask_.clone(); }
void setRefinementMask(const Mat &mask)
{
CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3));
refinement_mask_ = mask.clone();
}
double confThresh() const { return conf_thresh_; }
void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }
@@ -90,7 +97,10 @@ protected:
BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement)
: num_params_per_cam_(num_params_per_cam),
num_errs_per_measurement_(num_errs_per_measurement)
{ setConfThresh(1.); }
{
setRefinementMask(Mat::ones(3, 3, CV_8U));
setConfThresh(1.);
}
// Runs bundle adjustment
virtual void estimate(const std::vector<ImageFeatures> &features,
@@ -102,6 +112,9 @@ protected:
virtual void calcError(Mat &err) = 0;
virtual void calcJacobian(Mat &jac) = 0;
// 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine
Mat refinement_mask_;
int num_images_;
int total_num_matches_;
@@ -122,11 +135,13 @@ protected:
};
// Minimizes reprojection error
// Minimizes reprojection error.
// It can estimate focal length, aspect ratio, principal point.
// You can affect only on them via the refinement mask.
class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase
{
public:
BundleAdjusterReproj() : BundleAdjusterBase(6, 2) {}
BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {}
private:
void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
@@ -138,7 +153,8 @@ private:
};
// Minimizes sun of ray-to-ray distances
// Minimizes sun of ray-to-ray distances.
// It can estimate focal length. It ignores the refinement mask for now.
class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase
{
public:

2
modules/stitching/include/opencv2/stitching/detail/warpers_inl.hpp
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@@ -103,7 +103,7 @@ Rect WarperBase<P>::warpRoi(const Size &sz, const Mat &K, const Mat &R)
template <class P>
Rect WarperBase<P>::warpRoi(const Size &sz, const Mat &K, const Mat &R, const Mat &T)
Rect WarperBase<P>::warpRoi(const Size &/*sz*/, const Mat &/*K*/, const Mat &/*R*/, const Mat &/*T*/)
{
CV_Error(CV_StsNotImplemented, "translation support isn't implemented");
return Rect();

113
modules/stitching/src/motion_estimators.cpp
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@@ -247,13 +247,14 @@ void BundleAdjusterBase::estimate(const vector<ImageFeatures> &features,
void BundleAdjusterReproj::setUpInitialCameraParams(const vector<CameraParams> &cameras)
{
cam_params_.create(num_images_ * 6, 1, CV_64F);
cam_params_.create(num_images_ * 7, 1, CV_64F);
SVD svd;
for (int i = 0; i < num_images_; ++i)
{
cam_params_.at<double>(i * 6, 0) = cameras[i].focal;
cam_params_.at<double>(i * 6 + 1, 0) = cameras[i].ppx;
cam_params_.at<double>(i * 6 + 2, 0) = cameras[i].ppy;
cam_params_.at<double>(i * 7, 0) = cameras[i].focal;
cam_params_.at<double>(i * 7 + 1, 0) = cameras[i].ppx;
cam_params_.at<double>(i * 7 + 2, 0) = cameras[i].ppy;
cam_params_.at<double>(i * 7 + 3, 0) = cameras[i].aspect;
svd(cameras[i].R, SVD::FULL_UV);
Mat R = svd.u * svd.vt;
@@ -263,9 +264,9 @@ void BundleAdjusterReproj::setUpInitialCameraParams(const vector<CameraParams> &
Mat rvec;
Rodrigues(R, rvec);
CV_Assert(rvec.type() == CV_32F);
cam_params_.at<double>(i * 6 + 3, 0) = rvec.at<float>(0, 0);
cam_params_.at<double>(i * 6 + 4, 0) = rvec.at<float>(1, 0);
cam_params_.at<double>(i * 6 + 5, 0) = rvec.at<float>(2, 0);
cam_params_.at<double>(i * 7 + 4, 0) = rvec.at<float>(0, 0);
cam_params_.at<double>(i * 7 + 5, 0) = rvec.at<float>(1, 0);
cam_params_.at<double>(i * 7 + 6, 0) = rvec.at<float>(2, 0);
}
}
@@ -274,14 +275,15 @@ void BundleAdjusterReproj::obtainRefinedCameraParams(vector<CameraParams> &camer
{
for (int i = 0; i < num_images_; ++i)
{
cameras[i].focal = cam_params_.at<double>(i * 6, 0);
cameras[i].ppx = cam_params_.at<double>(i * 6 + 1, 0);
cameras[i].ppy = cam_params_.at<double>(i * 6 + 2, 0);
cameras[i].focal = cam_params_.at<double>(i * 7, 0);
cameras[i].ppx = cam_params_.at<double>(i * 7 + 1, 0);
cameras[i].ppy = cam_params_.at<double>(i * 7 + 2, 0);
cameras[i].aspect = cam_params_.at<double>(i * 7 + 3, 0);
Mat rvec(3, 1, CV_64F);
rvec.at<double>(0, 0) = cam_params_.at<double>(i * 6 + 3, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(i * 6 + 4, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(i * 6 + 5, 0);
rvec.at<double>(0, 0) = cam_params_.at<double>(i * 7 + 4, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(i * 7 + 5, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(i * 7 + 6, 0);
Rodrigues(rvec, cameras[i].R);
Mat tmp;
@@ -300,26 +302,28 @@ void BundleAdjusterReproj::calcError(Mat &err)
{
int i = edges_[edge_idx].first;
int j = edges_[edge_idx].second;
double f1 = cam_params_.at<double>(i * 6, 0);
double f2 = cam_params_.at<double>(j * 6, 0);
double ppx1 = cam_params_.at<double>(i * 6 + 1, 0);
double ppx2 = cam_params_.at<double>(j * 6 + 1, 0);
double ppy1 = cam_params_.at<double>(i * 6 + 2, 0);
double ppy2 = cam_params_.at<double>(j * 6 + 2, 0);
double f1 = cam_params_.at<double>(i * 7, 0);
double f2 = cam_params_.at<double>(j * 7, 0);
double ppx1 = cam_params_.at<double>(i * 7 + 1, 0);
double ppx2 = cam_params_.at<double>(j * 7 + 1, 0);
double ppy1 = cam_params_.at<double>(i * 7 + 2, 0);
double ppy2 = cam_params_.at<double>(j * 7 + 2, 0);
double a1 = cam_params_.at<double>(i * 7 + 3, 0);
double a2 = cam_params_.at<double>(j * 7 + 3, 0);
double R1[9];
Mat R1_(3, 3, CV_64F, R1);
Mat rvec(3, 1, CV_64F);
rvec.at<double>(0, 0) = cam_params_.at<double>(i * 6 + 3, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(i * 6 + 4, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(i * 6 + 5, 0);
rvec.at<double>(0, 0) = cam_params_.at<double>(i * 7 + 4, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(i * 7 + 5, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(i * 7 + 6, 0);
Rodrigues(rvec, R1_);
double R2[9];
Mat R2_(3, 3, CV_64F, R2);
rvec.at<double>(0, 0) = cam_params_.at<double>(j * 6 + 3, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(j * 6 + 4, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(j * 6 + 5, 0);
rvec.at<double>(0, 0) = cam_params_.at<double>(j * 7 + 4, 0);
rvec.at<double>(1, 0) = cam_params_.at<double>(j * 7 + 5, 0);
rvec.at<double>(2, 0) = cam_params_.at<double>(j * 7 + 6, 0);
Rodrigues(rvec, R2_);
const ImageFeatures& features1 = features_[i];
@@ -328,11 +332,11 @@ void BundleAdjusterReproj::calcError(Mat &err)
Mat_<double> K1 = Mat::eye(3, 3, CV_64F);
K1(0,0) = f1; K1(0,2) = ppx1;
K1(1,1) = f1; K1(1,2) = ppy1;
K1(1,1) = f1*a1; K1(1,2) = ppy1;
Mat_<double> K2 = Mat::eye(3, 3, CV_64F);
K2(0,0) = f2; K2(0,2) = ppx2;
K2(1,1) = f2; K2(1,2) = ppy2;
K2(1,1) = f2*a2; K2(1,2) = ppy2;
Mat_<double> H = K2 * R2_.inv() * R1_ * K1.inv();
@@ -358,22 +362,63 @@ void BundleAdjusterReproj::calcError(Mat &err)
void BundleAdjusterReproj::calcJacobian(Mat &jac)
{
jac.create(total_num_matches_ * 2, num_images_ * 6, CV_64F);
jac.create(total_num_matches_ * 2, num_images_ * 7, CV_64F);
jac.setTo(0);
double val;
const double step = 1e-4;
for (int i = 0; i < num_images_; ++i)
{
for (int j = 0; j < 6; ++j)
if (refinement_mask_.at<uchar>(0, 0))
{
val = cam_params_.at<double>(i * 6 + j, 0);
cam_params_.at<double>(i * 6 + j, 0) = val - step;
val = cam_params_.at<double>(i * 7, 0);
cam_params_.at<double>(i * 7, 0) = val - step;
calcError(err1_);
cam_params_.at<double>(i * 6 + j, 0) = val + step;
cam_params_.at<double>(i * 7, 0) = val + step;
calcError(err2_);
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 6 + j));
cam_params_.at<double>(i * 6 + j, 0) = val;
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7));
cam_params_.at<double>(i * 7, 0) = val;
}
if (refinement_mask_.at<uchar>(0, 2))
{
val = cam_params_.at<double>(i * 7 + 1, 0);
cam_params_.at<double>(i * 7 + 1, 0) = val - step;
calcError(err1_);
cam_params_.at<double>(i * 7 + 1, 0) = val + step;
calcError(err2_);
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 1));
cam_params_.at<double>(i * 7 + 1, 0) = val;
}
if (refinement_mask_.at<uchar>(1, 2))
{
val = cam_params_.at<double>(i * 7 + 2, 0);
cam_params_.at<double>(i * 7 + 2, 0) = val - step;
calcError(err1_);
cam_params_.at<double>(i * 7 + 2, 0) = val + step;
calcError(err2_);
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 2));
cam_params_.at<double>(i * 7 + 2, 0) = val;
}
if (refinement_mask_.at<uchar>(1, 1))
{
val = cam_params_.at<double>(i * 7 + 3, 0);
cam_params_.at<double>(i * 7 + 3, 0) = val - step;
calcError(err1_);
cam_params_.at<double>(i * 7 + 3, 0) = val + step;
calcError(err2_);
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 3));
cam_params_.at<double>(i * 7 + 3, 0) = val;
}
for (int j = 4; j < 7; ++j)
{
val = cam_params_.at<double>(i * 7 + j, 0);
cam_params_.at<double>(i * 7 + j, 0) = val - step;
calcError(err1_);
cam_params_.at<double>(i * 7 + j, 0) = val + step;
calcError(err2_);
calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + j));
cam_params_.at<double>(i * 7 + j, 0) = val;
}
}
}