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replaced tabs by spaces
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6a6f24b170
commit
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@ -100,7 +100,7 @@ protected:
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double tau;
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double lambda;
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double theta;
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double gamma;
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double gamma;
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int nscales;
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int warps;
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double epsilon;
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@ -111,7 +111,7 @@ protected:
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int medianFiltering;
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private:
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void procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2);
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void procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2, Mat_<float>& u3);
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bool procOneScale_ocl(const UMat& I0, const UMat& I1, UMat& u1, UMat& u2);
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@ -121,8 +121,8 @@ private:
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std::vector<Mat_<float> > I0s;
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std::vector<Mat_<float> > I1s;
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std::vector<Mat_<float> > u1s;
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std::vector<Mat_<float> > u2s;
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std::vector<Mat_<float> > u3s;
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std::vector<Mat_<float> > u2s;
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std::vector<Mat_<float> > u3s;
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Mat_<float> I1x_buf;
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Mat_<float> I1y_buf;
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@ -138,25 +138,26 @@ private:
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Mat_<float> rho_c_buf;
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Mat_<float> v1_buf;
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Mat_<float> v2_buf;
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Mat_<float> v2_buf;
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Mat_<float> v3_buf;
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Mat_<float> p11_buf;
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Mat_<float> p12_buf;
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Mat_<float> p21_buf;
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Mat_<float> p22_buf;
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Mat_<float> p31_buf;
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Mat_<float> p32_buf;
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Mat_<float> p22_buf;
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Mat_<float> p31_buf;
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Mat_<float> p32_buf;
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Mat_<float> div_p1_buf;
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Mat_<float> div_p2_buf;
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Mat_<float> div_p3_buf;
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Mat_<float> div_p2_buf;
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Mat_<float> div_p3_buf;
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Mat_<float> u1x_buf;
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Mat_<float> u1y_buf;
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Mat_<float> u2x_buf;
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Mat_<float> u2y_buf;
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Mat_<float> u3x_buf;
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Mat_<float> u3y_buf;
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Mat_<float> u2y_buf;
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Mat_<float> u3x_buf;
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Mat_<float> u3y_buf;
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} dm;
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struct dataUMat
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{
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@ -350,7 +351,7 @@ OpticalFlowDual_TVL1::OpticalFlowDual_TVL1()
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nscales = 5;
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warps = 5;
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epsilon = 0.01;
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gamma = 1.;
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gamma = 0.01;
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innerIterations = 30;
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outerIterations = 10;
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useInitialFlow = false;
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@ -375,15 +376,15 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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dm.I0s.resize(nscales);
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dm.I1s.resize(nscales);
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dm.u1s.resize(nscales);
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dm.u2s.resize(nscales);
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dm.u3s.resize(nscales);
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dm.u2s.resize(nscales);
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dm.u3s.resize(nscales);
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I0.convertTo(dm.I0s[0], dm.I0s[0].depth(), I0.depth() == CV_8U ? 1.0 : 255.0);
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I1.convertTo(dm.I1s[0], dm.I1s[0].depth(), I1.depth() == CV_8U ? 1.0 : 255.0);
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dm.u1s[0].create(I0.size());
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dm.u2s[0].create(I0.size());
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dm.u3s[0].create(I0.size());
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dm.u2s[0].create(I0.size());
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dm.u3s[0].create(I0.size());
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if (useInitialFlow)
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{
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@ -405,25 +406,26 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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dm.rho_c_buf.create(I0.size());
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dm.v1_buf.create(I0.size());
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dm.v2_buf.create(I0.size());
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dm.v2_buf.create(I0.size());
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dm.v3_buf.create(I0.size());
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dm.p11_buf.create(I0.size());
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dm.p12_buf.create(I0.size());
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dm.p21_buf.create(I0.size());
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dm.p22_buf.create(I0.size());
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dm.p31_buf.create(I0.size());
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dm.p32_buf.create(I0.size());
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dm.p22_buf.create(I0.size());
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dm.p31_buf.create(I0.size());
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dm.p32_buf.create(I0.size());
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dm.div_p1_buf.create(I0.size());
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dm.div_p2_buf.create(I0.size());
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dm.div_p3_buf.create(I0.size());
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dm.div_p2_buf.create(I0.size());
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dm.div_p3_buf.create(I0.size());
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dm.u1x_buf.create(I0.size());
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dm.u1y_buf.create(I0.size());
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dm.u2x_buf.create(I0.size());
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dm.u2y_buf.create(I0.size());
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dm.u3x_buf.create(I0.size());
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dm.u3y_buf.create(I0.size());
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dm.u2y_buf.create(I0.size());
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dm.u3x_buf.create(I0.size());
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dm.u3y_buf.create(I0.size());
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// create the scales
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for (int s = 1; s < nscales; ++s)
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@ -448,21 +450,21 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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else
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{
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dm.u1s[s].create(dm.I0s[s].size());
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dm.u2s[s].create(dm.I0s[s].size());
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dm.u2s[s].create(dm.I0s[s].size());
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}
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dm.u3s[s].create(dm.I0s[s].size());
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dm.u3s[s].create(dm.I0s[s].size());
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}
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if (!useInitialFlow)
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{
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dm.u1s[nscales - 1].setTo(Scalar::all(0));
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dm.u2s[nscales - 1].setTo(Scalar::all(0));
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}
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dm.u3s[nscales - 1].setTo(Scalar::all(0));
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}
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dm.u3s[nscales - 1].setTo(Scalar::all(0));
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// pyramidal structure for computing the optical flow
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for (int s = nscales - 1; s >= 0; --s)
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{
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// compute the optical flow at the current scale
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procOneScale(dm.I0s[s], dm.I1s[s], dm.u1s[s], dm.u2s[s]);
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procOneScale(dm.I0s[s], dm.I1s[s], dm.u1s[s], dm.u2s[s], dm.u3s[s]);
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// if this was the last scale, finish now
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if (s == 0)
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@ -472,7 +474,7 @@ void OpticalFlowDual_TVL1::calc(InputArray _I0, InputArray _I1, InputOutputArray
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// zoom the optical flow for the next finer scale
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resize(dm.u1s[s], dm.u1s[s - 1], dm.I0s[s - 1].size());
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resize(dm.u2s[s], dm.u2s[s - 1], dm.I0s[s - 1].size());
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resize(dm.u2s[s], dm.u2s[s - 1], dm.I0s[s - 1].size());
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resize(dm.u3s[s], dm.u3s[s - 1], dm.I0s[s - 1].size());
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// scale the optical flow with the appropriate zoom factor (don't scale u3!)
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@ -888,10 +890,10 @@ void CalcGradRhoBody::operator() (const Range& range) const
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// compute the constant part of the rho function
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rhoRow[x] = (I1wRow[x] - I1wxRow[x] * u1Row[x] - I1wyRow[x] * u2Row[x] - I0Row[x]);
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//It = I1wRow[x] - I0Row[x]
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//(u - u0)*i_X = I1wxRow[x] * u1Row[x]
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//(v - v0)*i_Y = I1wyRow[x] * u2Row[x]
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// gamma * w = gamma * u3
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//It = I1wRow[x] - I0Row[x]
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//(u - u0)*i_X = I1wxRow[x] * u1Row[x]
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//(v - v0)*i_Y = I1wyRow[x] * u2Row[x]
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// gamma * w = gamma * u3
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}
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}
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}
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@ -931,15 +933,15 @@ struct EstimateVBody : ParallelLoopBody
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Mat_<float> I1wx;
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Mat_<float> I1wy;
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Mat_<float> u1;
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Mat_<float> u2;
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Mat_<float> u3;
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Mat_<float> u2;
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Mat_<float> u3;
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Mat_<float> grad;
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Mat_<float> rho_c;
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mutable Mat_<float> v1;
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mutable Mat_<float> v2;
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mutable Mat_<float> v3;
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mutable Mat_<float> v2;
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mutable Mat_<float> v3;
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float l_t;
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float gamma;
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float gamma;
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};
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void EstimateVBody::operator() (const Range& range) const
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@ -949,14 +951,14 @@ void EstimateVBody::operator() (const Range& range) const
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const float* I1wxRow = I1wx[y];
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const float* I1wyRow = I1wy[y];
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const float* u1Row = u1[y];
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const float* u2Row = u2[y];
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const float* u3Row = u3[y];
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const float* u2Row = u2[y];
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const float* u3Row = u3[y];
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const float* gradRow = grad[y];
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const float* rhoRow = rho_c[y];
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float* v1Row = v1[y];
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float* v2Row = v2[y];
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float* v3Row = v3[y];
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float* v2Row = v2[y];
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float* v3Row = v3[y];
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for (int x = 0; x < I1wx.cols; ++x)
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{
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@ -964,37 +966,37 @@ void EstimateVBody::operator() (const Range& range) const
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float d1 = 0.0f;
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float d2 = 0.0f;
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float d3 = 0.0f;
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float d3 = 0.0f;
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// add d3 for 3 cases
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if (rho < -l_t * gradRow[x])
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{
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d1 = l_t * I1wxRow[x];
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d2 = l_t * I1wyRow[x];
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d3 = l_t * gamma;
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d3 = l_t * gamma;
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}
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else if (rho > l_t * gradRow[x])
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{
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d1 = -l_t * I1wxRow[x];
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d2 = -l_t * I1wyRow[x];
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d3 = -l_t * gamma;
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d2 = -l_t * I1wyRow[x];
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d3 = -l_t * gamma;
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}
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else if (gradRow[x] > std::numeric_limits<float>::epsilon())
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{
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float fi = -rho / gradRow[x];
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d1 = fi * I1wxRow[x];
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d2 = fi * I1wyRow[x];
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d3 = fi * gamma;
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d3 = fi * gamma;
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}
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v1Row[x] = u1Row[x] + d1;
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v2Row[x] = u2Row[x] + d2;
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v3Row[x] = u3Row[x] + d3;
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v2Row[x] = u2Row[x] + d2;
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v3Row[x] = u3Row[x] + d3;
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}
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}
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}
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void estimateV(const Mat_<float>& I1wx, const Mat_<float>& I1wy, const Mat_<float>& u1, const Mat_<float>& u2, const Mat_<float>& u3, const Mat_<float>& grad, const Mat_<float>& rho_c,
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Mat_<float>& v1, Mat_<float>& v2, Mat_<float>& v3, float l_t, float gamma)
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Mat_<float>& v1, Mat_<float>& v2, Mat_<float>& v3, float l_t, float gamma)
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{
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CV_DbgAssert( I1wy.size() == I1wx.size() );
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CV_DbgAssert( u1.size() == I1wx.size() );
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@ -1011,15 +1013,15 @@ void estimateV(const Mat_<float>& I1wx, const Mat_<float>& I1wy, const Mat_<floa
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body.I1wx = I1wx;
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body.I1wy = I1wy;
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body.u1 = u1;
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body.u2 = u2;
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body.u3 = u3;
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body.u2 = u2;
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body.u3 = u3;
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body.grad = grad;
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body.rho_c = rho_c;
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body.v1 = v1;
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body.v2 = v2;
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body.v3 = v3;
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body.l_t = l_t;
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body.gamma = gamma;
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body.v2 = v2;
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body.v3 = v3;
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body.l_t = l_t;
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body.gamma = gamma;
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parallel_for_(Range(0, I1wx.rows), body);
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}
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@ -1027,36 +1029,45 @@ void estimateV(const Mat_<float>& I1wx, const Mat_<float>& I1wy, const Mat_<floa
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////////////////////////////////////////////////////////////
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// estimateU
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float estimateU(const Mat_<float>& v1, const Mat_<float>& v2, const Mat_<float>& div_p1, const Mat_<float>& div_p2, Mat_<float>& u1, Mat_<float>& u2, float theta)
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float estimateU(const Mat_<float>& v1, const Mat_<float>& v2, const Mat_<float>& v3,
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const Mat_<float>& div_p1, const Mat_<float>& div_p2, const Mat_<float>& div_p3,
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Mat_<float>& u1, Mat_<float>& u2, Mat_<float>& u3,
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float theta, float gamma)
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{
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CV_DbgAssert( v2.size() == v1.size() );
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CV_DbgAssert( v3.size() == v1.size() );
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CV_DbgAssert( div_p1.size() == v1.size() );
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CV_DbgAssert( div_p2.size() == v1.size() );
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CV_DbgAssert( div_p3.size() == v1.size() );
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CV_DbgAssert( u1.size() == v1.size() );
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CV_DbgAssert( u2.size() == v1.size() );
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CV_DbgAssert( u3.size() == v1.size() );
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float error = 0.0f;
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for (int y = 0; y < v1.rows; ++y)
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{
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const float* v1Row = v1[y];
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const float* v2Row = v2[y];
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const float* v2Row = v2[y];
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const float* v3Row = v3[y];
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const float* divP1Row = div_p1[y];
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const float* divP2Row = div_p2[y];
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const float* divP2Row = div_p2[y];
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const float* divP3Row = div_p3[y];
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float* u1Row = u1[y];
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float* u2Row = u2[y];
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float* u2Row = u2[y];
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float* u3Row = u3[y];
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for (int x = 0; x < v1.cols; ++x)
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{
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const float u1k = u1Row[x];
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const float u2k = u2Row[x];
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const float u2k = u2Row[x];
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const float u3k = u3Row[x];
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u1Row[x] = v1Row[x] + theta * divP1Row[x];
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u2Row[x] = v2Row[x] + theta * divP2Row[x];
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//u3
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error += (u1Row[x] - u1k) * (u1Row[x] - u1k) + (u2Row[x] - u2k) * (u2Row[x] - u2k);
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u2Row[x] = v2Row[x] + theta * divP2Row[x];
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u3Row[x] = v3Row[x] + theta * divP3Row[x];
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error += (u1Row[x] - u1k) * (u1Row[x] - u1k) + (u2Row[x] - u2k) * (u2Row[x] - u2k) + (u3Row[x] - u3k) * (u3Row[x] - u3k);
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}
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}
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@ -1073,11 +1084,15 @@ struct EstimateDualVariablesBody : ParallelLoopBody
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Mat_<float> u1x;
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Mat_<float> u1y;
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Mat_<float> u2x;
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Mat_<float> u2y;
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Mat_<float> u2y;
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Mat_<float> u3x;
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Mat_<float> u3y;
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mutable Mat_<float> p11;
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mutable Mat_<float> p12;
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mutable Mat_<float> p21;
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mutable Mat_<float> p22;
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mutable Mat_<float> p22;
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mutable Mat_<float> p31;
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mutable Mat_<float> p32;
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float taut;
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};
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@ -1088,50 +1103,71 @@ void EstimateDualVariablesBody::operator() (const Range& range) const
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const float* u1xRow = u1x[y];
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const float* u1yRow = u1y[y];
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const float* u2xRow = u2x[y];
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const float* u2yRow = u2y[y];
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const float* u2yRow = u2y[y];
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const float* u3xRow = u3x[y];
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const float* u3yRow = u3y[y];
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float* p11Row = p11[y];
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float* p12Row = p12[y];
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float* p21Row = p21[y];
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float* p22Row = p22[y];
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float* p22Row = p22[y];
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float* p31Row = p31[y];
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float* p32Row = p32[y];
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for (int x = 0; x < u1x.cols; ++x)
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{
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const float g1 = static_cast<float>(hypot(u1xRow[x], u1yRow[x]));
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const float g2 = static_cast<float>(hypot(u2xRow[x], u2yRow[x]));
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const float g2 = static_cast<float>(hypot(u2xRow[x], u2yRow[x]));
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const float g3 = static_cast<float>(hypot(u3xRow[x], u3yRow[x]));
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|
||||
const float ng1 = 1.0f + taut * g1;
|
||||
const float ng2 = 1.0f + taut * g2;
|
||||
const float ng2 = 1.0f + taut * g2;
|
||||
const float ng3 = 1.0f + taut * g3;
|
||||
|
||||
p11Row[x] = (p11Row[x] + taut * u1xRow[x]) / ng1;
|
||||
p12Row[x] = (p12Row[x] + taut * u1yRow[x]) / ng1;
|
||||
p21Row[x] = (p21Row[x] + taut * u2xRow[x]) / ng2;
|
||||
p22Row[x] = (p22Row[x] + taut * u2yRow[x]) / ng2;
|
||||
p22Row[x] = (p22Row[x] + taut * u2yRow[x]) / ng2;
|
||||
p31Row[x] = (p31Row[x] + taut * u3xRow[x]) / ng3;
|
||||
p32Row[x] = (p32Row[x] + taut * u3yRow[x]) / ng3;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void estimateDualVariables(const Mat_<float>& u1x, const Mat_<float>& u1y, const Mat_<float>& u2x, const Mat_<float>& u2y,
|
||||
Mat_<float>& p11, Mat_<float>& p12, Mat_<float>& p21, Mat_<float>& p22, float taut)
|
||||
void estimateDualVariables(const Mat_<float>& u1x, const Mat_<float>& u1y,
|
||||
const Mat_<float>& u2x, const Mat_<float>& u2y,
|
||||
const Mat_<float>& u3x, const Mat_<float>& u3y,
|
||||
Mat_<float>& p11, Mat_<float>& p12,
|
||||
Mat_<float>& p21, Mat_<float>& p22,
|
||||
Mat_<float>& p31, Mat_<float>& p32,
|
||||
float taut)
|
||||
{
|
||||
CV_DbgAssert( u1y.size() == u1x.size() );
|
||||
CV_DbgAssert( u2x.size() == u1x.size() );
|
||||
CV_DbgAssert( u3x.size() == u1x.size() );
|
||||
CV_DbgAssert( u2y.size() == u1x.size() );
|
||||
CV_DbgAssert( u3y.size() == u1x.size() );
|
||||
CV_DbgAssert( p11.size() == u1x.size() );
|
||||
CV_DbgAssert( p12.size() == u1x.size() );
|
||||
CV_DbgAssert( p21.size() == u1x.size() );
|
||||
CV_DbgAssert( p22.size() == u1x.size() );
|
||||
CV_DbgAssert( p31.size() == u1x.size() );
|
||||
CV_DbgAssert( p32.size() == u1x.size() );
|
||||
|
||||
EstimateDualVariablesBody body;
|
||||
|
||||
body.u1x = u1x;
|
||||
body.u1y = u1y;
|
||||
body.u2x = u2x;
|
||||
body.u2y = u2y;
|
||||
body.u2y = u2y;
|
||||
body.u3x = u3x;
|
||||
body.u3y = u3y;
|
||||
body.p11 = p11;
|
||||
body.p12 = p12;
|
||||
body.p21 = p21;
|
||||
body.p22 = p22;
|
||||
body.p22 = p22;
|
||||
body.p31 = p31;
|
||||
body.p32 = p32;
|
||||
body.taut = taut;
|
||||
|
||||
parallel_for_(Range(0, u1x.rows), body);
|
||||
@ -1225,7 +1261,7 @@ bool OpticalFlowDual_TVL1::procOneScale_ocl(const UMat& I0, const UMat& I1, UMat
|
||||
return true;
|
||||
}
|
||||
|
||||
void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2)
|
||||
void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>& I1, Mat_<float>& u1, Mat_<float>& u2, Mat_<float>& u3)
|
||||
{
|
||||
const float scaledEpsilon = static_cast<float>(epsilon * epsilon * I0.size().area());
|
||||
|
||||
@ -1249,31 +1285,32 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
|
||||
Mat_<float> rho_c = dm.rho_c_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
|
||||
Mat_<float> v1 = dm.v1_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> v2 = dm.v2_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> v2 = dm.v2_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> v3 = dm.v3_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
|
||||
Mat_<float> p11 = dm.p11_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p12 = dm.p12_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p21 = dm.p21_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p22 = dm.p22_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p31 = dm.p31_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p32 = dm.p32_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p22 = dm.p22_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p31 = dm.p31_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> p32 = dm.p32_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
p11.setTo(Scalar::all(0));
|
||||
p12.setTo(Scalar::all(0));
|
||||
p21.setTo(Scalar::all(0));
|
||||
p22.setTo(Scalar::all(0));
|
||||
p31.setTo(Scalar::all(0));
|
||||
p32.setTo(Scalar::all(0));
|
||||
p22.setTo(Scalar::all(0));
|
||||
p31.setTo(Scalar::all(0));
|
||||
p32.setTo(Scalar::all(0));
|
||||
|
||||
Mat_<float> div_p1 = dm.div_p1_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> div_p2 = dm.div_p2_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> div_p3 = dm.div_p2_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> div_p2 = dm.div_p2_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> div_p3 = dm.div_p3_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
|
||||
Mat_<float> u1x = dm.u1x_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u1y = dm.u1y_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u2x = dm.u2x_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u2y = dm.u2y_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u3x = dm.u3x_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u3y = dm.u3y_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u2y = dm.u2y_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u3x = dm.u3x_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
Mat_<float> u3y = dm.u3y_buf(Rect(0, 0, I0.cols, I0.rows));
|
||||
|
||||
const float l_t = static_cast<float>(lambda * theta);
|
||||
const float taut = static_cast<float>(tau / theta);
|
||||
@ -1285,7 +1322,7 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
|
||||
remap(I1, I1w, flowMap1, flowMap2, INTER_CUBIC);
|
||||
remap(I1x, I1wx, flowMap1, flowMap2, INTER_CUBIC);
|
||||
remap(I1y, I1wy, flowMap1, flowMap2, INTER_CUBIC);
|
||||
//calculate I1(x+u0) and its gradient
|
||||
//calculate I1(x+u0) and its gradient
|
||||
calcGradRho(I0, I1w, I1wx, I1wy, u1, u2, grad, rho_c);
|
||||
|
||||
float error = std::numeric_limits<float>::max();
|
||||
@ -1298,21 +1335,23 @@ void OpticalFlowDual_TVL1::procOneScale(const Mat_<float>& I0, const Mat_<float>
|
||||
for (int n_inner = 0; error > scaledEpsilon && n_inner < innerIterations; ++n_inner)
|
||||
{
|
||||
// estimate the values of the variable (v1, v2) (thresholding operator TH)
|
||||
estimateV(I1wx, I1wy, u1, u2, grad, rho_c, v1, v2, l_t);
|
||||
estimateV(I1wx, I1wy, u1, u2, u3, grad, rho_c, v1, v2, v3, l_t, gamma);
|
||||
|
||||
// compute the divergence of the dual variable (p1, p2)
|
||||
// compute the divergence of the dual variable (p1, p2, p3)
|
||||
divergence(p11, p12, div_p1);
|
||||
divergence(p21, p22, div_p2);
|
||||
divergence(p21, p22, div_p2);
|
||||
divergence(p31, p32, div_p3);
|
||||
|
||||
// estimate the values of the optical flow (u1, u2)
|
||||
error = estimateU(v1, v2, div_p1, div_p2, u1, u2, static_cast<float>(theta));
|
||||
error = estimateU(v1, v2, v3, div_p1, div_p2, div_p3, u1, u2, u3, static_cast<float>(theta), gamma);
|
||||
|
||||
// compute the gradient of the optical flow (Du1, Du2)
|
||||
forwardGradient(u1, u1x, u1y);
|
||||
forwardGradient(u2, u2x, u2y);
|
||||
forwardGradient(u2, u2x, u2y);
|
||||
forwardGradient(u3, u3x, u3y);
|
||||
|
||||
// estimate the values of the dual variable (p1, p2)
|
||||
estimateDualVariables(u1x, u1y, u2x, u2y, p11, p12, p21, p22, taut);
|
||||
// estimate the values of the dual variable (p1, p2, p3)
|
||||
estimateDualVariables(u1x, u1y, u2x, u2y, u3x, u3y, p11, p12, p21, p22, p31, p32, taut);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1402,6 +1441,8 @@ CV_INIT_ALGORITHM(OpticalFlowDual_TVL1, "DenseOpticalFlow.DualTVL1",
|
||||
"inner iterations (between outlier filtering) used in the numerical scheme");
|
||||
obj.info()->addParam(obj, "outerIterations", obj.outerIterations, false, 0, 0,
|
||||
"outer iterations (number of inner loops) used in the numerical scheme");
|
||||
obj.info()->addParam(obj, "gamma", obj.gamma, false, 0, 0,
|
||||
"coefficient for additional Ali term");
|
||||
obj.info()->addParam(obj, "useInitialFlow", obj.useInitialFlow))
|
||||
|
||||
} // namespace
|
||||
|
Loading…
Reference in New Issue
Block a user