CV_Assert( I0.type() == I1.type() );
CV_Assert( !useInitialFlow || (_flow.size() == I0.size() && _flow.type() == CV_32FC2) );
CV_Assert( nscales > 0 );
- bool use_gamma = gamma != 0;
+ bool use_gamma = gamma != 0;
// allocate memory for the pyramid structure
dm.I0s.resize(nscales);
dm.I1s.resize(nscales);
dm.u1s.resize(nscales);
dm.u2s.resize(nscales);
- dm.u3s.resize(nscales);
+ dm.u3s.resize(nscales);
I0.convertTo(dm.I0s[0], dm.I0s[0].depth(), I0.depth() == CV_8U ? 1.0 : 255.0);
I1.convertTo(dm.I1s[0], dm.I1s[0].depth(), I1.depth() == CV_8U ? 1.0 : 255.0);
dm.u1s[0].create(I0.size());
dm.u2s[0].create(I0.size());
- if (use_gamma) dm.u3s[0].create(I0.size());
+ if (use_gamma) dm.u3s[0].create(I0.size());
if (useInitialFlow)
{
dm.v1_buf.create(I0.size());
dm.v2_buf.create(I0.size());
- dm.v3_buf.create(I0.size());
+ dm.v3_buf.create(I0.size());
dm.p11_buf.create(I0.size());
dm.p12_buf.create(I0.size());
dm.p21_buf.create(I0.size());
dm.p22_buf.create(I0.size());
- dm.p31_buf.create(I0.size());
- dm.p32_buf.create(I0.size());
+ dm.p31_buf.create(I0.size());
+ dm.p32_buf.create(I0.size());
dm.div_p1_buf.create(I0.size());
dm.div_p2_buf.create(I0.size());
- dm.div_p3_buf.create(I0.size());
+ dm.div_p3_buf.create(I0.size());
dm.u1x_buf.create(I0.size());
dm.u1y_buf.create(I0.size());
dm.u2x_buf.create(I0.size());
dm.u2y_buf.create(I0.size());
dm.u3x_buf.create(I0.size());
- dm.u3y_buf.create(I0.size());
+ dm.u3y_buf.create(I0.size());
// create the scales
for (int s = 1; s < nscales; ++s)
dm.u1s[s].create(dm.I0s[s].size());
dm.u2s[s].create(dm.I0s[s].size());
}
- if (use_gamma) dm.u3s[s].create(dm.I0s[s].size());
+ if (use_gamma) dm.u3s[s].create(dm.I0s[s].size());
}
if (!useInitialFlow)
{
dm.u1s[nscales - 1].setTo(Scalar::all(0));
dm.u2s[nscales - 1].setTo(Scalar::all(0));
}
- if (use_gamma) dm.u3s[nscales - 1].setTo(Scalar::all(0));
+ if (use_gamma) dm.u3s[nscales - 1].setTo(Scalar::all(0));
// pyramidal structure for computing the optical flow
for (int s = nscales - 1; s >= 0; --s)
{
// zoom the optical flow for the next finer scale
resize(dm.u1s[s], dm.u1s[s - 1], dm.I0s[s - 1].size());
resize(dm.u2s[s], dm.u2s[s - 1], dm.I0s[s - 1].size());
- if (use_gamma) resize(dm.u3s[s], dm.u3s[s - 1], dm.I0s[s - 1].size());
+ if (use_gamma) resize(dm.u3s[s], dm.u3s[s - 1], dm.I0s[s - 1].size());
// scale the optical flow with the appropriate zoom factor (don't scale u3!)
multiply(dm.u1s[s - 1], Scalar::all(1 / scaleStep), dm.u1s[s - 1]);
void EstimateVBody::operator() (const Range& range) const
{
- bool use_gamma = gamma != 0;
+ bool use_gamma = gamma != 0;
for (int y = range.start; y < range.end; ++y)
{
const float* I1wxRow = I1wx[y];
float* v1Row = v1[y];
float* v2Row = v2[y];
- float* v3Row = use_gamma ? v3[y]:NULL;
+ float* v3Row = use_gamma ? v3[y]:NULL;
for (int x = 0; x < I1wx.cols; ++x)
- {
- const float rho = use_gamma ? rhoRow[x] + (I1wxRow[x] * u1Row[x] + I1wyRow[x] * u2Row[x]) + gamma * u3Row[x] :
- rhoRow[x] + (I1wxRow[x] * u1Row[x] + I1wyRow[x] * u2Row[x]);
+ {
+ const float rho = use_gamma ? rhoRow[x] + (I1wxRow[x] * u1Row[x] + I1wyRow[x] * u2Row[x]) + gamma * u3Row[x] :
+ rhoRow[x] + (I1wxRow[x] * u1Row[x] + I1wyRow[x] * u2Row[x]);
float d1 = 0.0f;
float d2 = 0.0f;
float d3 = 0.0f;
{
d1 = l_t * I1wxRow[x];
d2 = l_t * I1wyRow[x];
- if (use_gamma) d3 = l_t * gamma;
+ if (use_gamma) d3 = l_t * gamma;
}
else if (rho > l_t * gradRow[x])
{
d1 = -l_t * I1wxRow[x];
d2 = -l_t * I1wyRow[x];
- if (use_gamma) d3 = -l_t * gamma;
+ if (use_gamma) d3 = -l_t * gamma;
}
else if (gradRow[x] > std::numeric_limits<float>::epsilon())
{
float fi = -rho / gradRow[x];
d1 = fi * I1wxRow[x];
d2 = fi * I1wyRow[x];
- if (use_gamma) d3 = fi * gamma;
+ if (use_gamma) d3 = fi * gamma;
}
v1Row[x] = u1Row[x] + d1;
v2Row[x] = u2Row[x] + d2;
- if (use_gamma) v3Row[x] = u3Row[x] + d3;
+ if (use_gamma) v3Row[x] = u3Row[x] + d3;
}
}
}
CV_DbgAssert( v2.size() == I1wx.size() );
EstimateVBody body;
- bool use_gamma = gamma != 0;
+ bool use_gamma = gamma != 0;
body.I1wx = I1wx;
body.I1wy = I1wy;
body.u1 = u1;
body.u2 = u2;
- if (use_gamma) body.u3 = u3;
+ if (use_gamma) body.u3 = u3;
body.grad = grad;
body.rho_c = rho_c;
body.v1 = v1;
body.v2 = v2;
- if (use_gamma) body.v3 = v3;
+ if (use_gamma) body.v3 = v3;
body.l_t = l_t;
body.gamma = gamma;
parallel_for_(Range(0, I1wx.rows), body);
CV_DbgAssert( u1.size() == v1.size() );
CV_DbgAssert( u2.size() == v1.size() );
- float error = 0.0f;
- bool use_gamma = gamma != 0;
+ float error = 0.0f;
+ bool use_gamma = gamma != 0;
for (int y = 0; y < v1.rows; ++y)
{
const float* v1Row = v1[y];
u1Row[x] = v1Row[x] + theta * divP1Row[x];
u2Row[x] = v2Row[x] + theta * divP2Row[x];
- if (use_gamma) u3Row[x] = v3Row[x] + theta * divP3Row[x];
+ if (use_gamma) u3Row[x] = v3Row[x] + theta * divP3Row[x];
error += use_gamma?(u1Row[x] - u1k) * (u1Row[x] - u1k) + (u2Row[x] - u2k) * (u2Row[x] - u2k) + (u3Row[x] - u3k) * (u3Row[x] - u3k):
- (u1Row[x] - u1k) * (u1Row[x] - u1k) + (u2Row[x] - u2k) * (u2Row[x] - u2k);
+ (u1Row[x] - u1k) * (u1Row[x] - u1k) + (u2Row[x] - u2k) * (u2Row[x] - u2k);
}
}
mutable Mat_<float> p31;
mutable Mat_<float> p32;
float taut;
- bool use_gamma;
+ bool use_gamma;
};
void EstimateDualVariablesBody::operator() (const Range& range) const
const float ng1 = 1.0f + taut * g1;
const float ng2 = 1.0f + taut * g2;
- const float ng3 = 1.0f + taut * g3;
+ 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;
- if (use_gamma) p31Row[x] = (p31Row[x] + taut * u3xRow[x]) / ng3;
- if (use_gamma) p32Row[x] = (p32Row[x] + taut * u3yRow[x]) / ng3;
+ if (use_gamma) p31Row[x] = (p31Row[x] + taut * u3xRow[x]) / ng3;
+ if (use_gamma) p32Row[x] = (p32Row[x] + taut * u3yRow[x]) / ng3;
}
}
}
body.p31 = p31;
body.p32 = p32;
body.taut = taut;
- body.use_gamma = use_gamma;
+ body.use_gamma = use_gamma;
parallel_for_(Range(0, u1x.rows), body);
}
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> v3 = dm.v3_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> 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));
- bool use_gamma = gamma != 0.;
- if (use_gamma) p31.setTo(Scalar::all(0));
- if (use_gamma) p32.setTo(Scalar::all(0));
+ p22.setTo(Scalar::all(0));
+ bool use_gamma = gamma != 0.;
+ if (use_gamma) p31.setTo(Scalar::all(0));
+ if (use_gamma) 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));
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, u3, grad, rho_c, v1, v2, v3, l_t, static_cast<float>(gamma));
+ estimateV(I1wx, I1wy, u1, u2, u3, grad, rho_c, v1, v2, v3, l_t, static_cast<float>(gamma));
// compute the divergence of the dual variable (p1, p2, p3)
divergence(p11, p12, div_p1);
divergence(p21, p22, div_p2);
- if (use_gamma) divergence(p31, p32, div_p3);
+ if (use_gamma) divergence(p31, p32, div_p3);
// estimate the values of the optical flow (u1, u2)
- error = estimateU(v1, v2, v3, div_p1, div_p2, div_p3, u1, u2, u3, static_cast<float>(theta), static_cast<float>(gamma));
+ error = estimateU(v1, v2, v3, div_p1, div_p2, div_p3, u1, u2, u3, static_cast<float>(theta), static_cast<float>(gamma));
// compute the gradient of the optical flow (Du1, Du2)
forwardGradient(u1, u1x, u1y);
forwardGradient(u2, u2x, u2y);
- if (use_gamma) forwardGradient(u3, u3x, u3y);
+ if (use_gamma) forwardGradient(u3, u3x, u3y);
// estimate the values of the dual variable (p1, p2, p3)
estimateDualVariables(u1x, u1y, u2x, u2y, u3x, u3y, p11, p12, p21, p22, p31, p32, taut, use_gamma);