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Added linear similarity estimation into videostab module

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This commit is contained in:
Alexey Spizhevoy 2012-03-30 09:44:32 +00:00
parent 1af9b8ecab
commit 99f29b75a1
4 changed files with 46 additions and 5 deletions
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8
modules/videostab/include/opencv2/videostab/global_motion.hpp
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@ -57,7 +57,8 @@ enum MotionModel
{
TRANSLATION = 0,
TRANSLATION_AND_SCALE = 1,
AFFINE = 2
LINEAR_SIMILARITY = 2,
AFFINE = 3
};
CV_EXPORTS Mat estimateGlobalMotionLeastSquares(
@ -74,9 +75,10 @@ struct CV_EXPORTS RansacParams
RansacParams(int size, float thresh, float eps, float prob)
: size(size), thresh(thresh), eps(eps), prob(prob) {}
static RansacParams affine2dMotionStd() { return RansacParams(6, 0.5f, 0.5f, 0.99f); }
static RansacParams translationAndScale2dMotionStd() { return RansacParams(3, 0.5f, 0.5f, 0.99f); }
static RansacParams translationMotionStd() { return RansacParams(2, 0.5f, 0.5f, 0.99f); }
static RansacParams translationAndScale2dMotionStd() { return RansacParams(3, 0.5f, 0.5f, 0.99f); }
static RansacParams linearSimilarityMotionStd() { return RansacParams(4, 0.5f, 0.5f, 0.99f); }
static RansacParams affine2dMotionStd() { return RansacParams(6, 0.5f, 0.5f, 0.99f); }
};
CV_EXPORTS Mat estimateGlobalMotionRobust(

37
modules/videostab/src/global_motion.cpp
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@ -107,6 +107,41 @@ static Mat estimateGlobMotionLeastSquaresTranslationAndScale(
}
static Mat estimateGlobMotionLeastSquaresLinearSimilarity(
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
{
Mat_<float> A(2*npoints, 4), b(2*npoints, 1);
float *a0, *a1;
Point2f p0, p1;
for (int i = 0; i < npoints; ++i)
{
a0 = A[2*i];
a1 = A[2*i+1];
p0 = points0[i];
p1 = points1[i];
a0[0] = p0.x; a0[1] = p0.y; a0[2] = 1; a0[3] = 0;
a1[0] = p0.y; a1[1] = -p0.x; a1[2] = 0; a1[3] = 1;
b(2*i,0) = p1.x;
b(2*i+1,0) = p1.y;
}
Mat_<float> sol;
solve(A, b, sol, DECOMP_SVD);
if (rmse)
*rmse = static_cast<float>(norm(A*sol, b, NORM_L2) / sqrt(static_cast<double>(npoints)));
Mat_<float> M = Mat::eye(3, 3, CV_32F);
M(0,0) = M(1,1) = sol(0,0);
M(0,1) = sol(1,0);
M(1,0) = -sol(1,0);
M(0,2) = sol(2,0);
M(1,2) = sol(3,0);
return M;
}
static Mat estimateGlobMotionLeastSquaresAffine(
int npoints, const Point2f *points0, const Point2f *points1, float *rmse)
{
@ -149,6 +184,7 @@ Mat estimateGlobalMotionLeastSquares(
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
estimateGlobMotionLeastSquaresTranslationAndScale,
estimateGlobMotionLeastSquaresLinearSimilarity,
estimateGlobMotionLeastSquaresAffine };
int npoints = static_cast<int>(points0.size());
@ -165,6 +201,7 @@ Mat estimateGlobalMotionRobust(
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
estimateGlobMotionLeastSquaresTranslationAndScale,
estimateGlobMotionLeastSquaresLinearSimilarity,
estimateGlobMotionLeastSquaresAffine };
const int npoints = static_cast<int>(points0.size());

2
modules/videostab/src/stabilizer.cpp
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@ -266,7 +266,7 @@ void OnePassStabilizer::stabilizeFrame()
TwoPassStabilizer::TwoPassStabilizer()
{
setMotionStabilizer(new GaussianMotionFilter());
setEstimateTrimRatio(true);
setEstimateTrimRatio(false);
resetImpl();
}

4
samples/cpp/videostab.cpp
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@ -121,7 +121,7 @@ void printHelp()
cout << "OpenCV video stabilizer.\n"
"Usage: videostab <file_path> [arguments]\n\n"
"Arguments:\n"
" -m, --model=(transl|transl_and_scale|affine)\n"
" -m, --model=(transl|transl_and_scale|linear_sim|affine)\n"
" Set motion model. The default is affine.\n"
" --outlier-ratio=<float_number>\n"
" Outliers ratio in motion estimation. The default is 0.5.\n"
@ -259,6 +259,8 @@ int main(int argc, const char **argv)
motionEstimator->setMotionModel(TRANSLATION);
else if (cmd.get<string>("model") == "transl_and_scale")
motionEstimator->setMotionModel(TRANSLATION_AND_SCALE);
else if (cmd.get<string>("model") == "linear_sim")
motionEstimator->setMotionModel(LINEAR_SIMILARITY);
else if (cmd.get<string>("model") == "affine")
motionEstimator->setMotionModel(AFFINE);
else if (!cmd.get<string>("model").empty())