{
TRANSLATION = 0,
TRANSLATION_AND_SCALE = 1,
- AFFINE = 2
+ LINEAR_SIMILARITY = 2,
+ AFFINE = 3
};
CV_EXPORTS Mat estimateGlobalMotionLeastSquares(
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(
}
+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)
{
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
estimateGlobMotionLeastSquaresTranslationAndScale,
+ estimateGlobMotionLeastSquaresLinearSimilarity,
estimateGlobMotionLeastSquaresAffine };
int npoints = static_cast<int>(points0.size());
typedef Mat (*Impl)(int, const Point2f*, const Point2f*, float*);
static Impl impls[] = { estimateGlobMotionLeastSquaresTranslation,
estimateGlobMotionLeastSquaresTranslationAndScale,
+ estimateGlobMotionLeastSquaresLinearSimilarity,
estimateGlobMotionLeastSquaresAffine };
const int npoints = static_cast<int>(points0.size());
TwoPassStabilizer::TwoPassStabilizer()
{
setMotionStabilizer(new GaussianMotionFilter());
- setEstimateTrimRatio(true);
+ setEstimateTrimRatio(false);
resetImpl();
}
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"
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())