void ASMFitResult::toDiffPointList(vector< Point_<int> > &pV) const {
ShapeVec sv;
asmModel->projectParamToShape(params, sv);
sv.restoreToPointList(pV, transformation);
vector<Point_<int> > pV2;
toMeanPointList(pV2);
int i,len=pV.size();
for(i=0;i<len;i++){
pV[i].x-=pV2[i].x;
pV[i].y-=pV2[i].y;
}
}
void SimilarityTrans::transform(const ShapeVec &src, ShapeVec &dst) const{
int nP = src.nPoints();
dst.create(nP<<1, 1);
double xt, yt;
for (int i=0; i < nP; i++) {
xt = src.X(i);
yt = src.Y(i);
dst.X(i) = a * xt - b * yt + Xt;
dst.Y(i) = b * xt + a * yt + Yt;
}
}
void SimilarityTrans::invTransform(const ShapeVec &src, ShapeVec &dst) const{
int nP = src.nPoints();
double x11, x12, x21, x22;
x11 = a/(a*a+b*b);
x12 = b/(a*a+b*b);
x21 = -b/(a*a+b*b);
x22 = a/(a*a+b*b);
dst.create(nP<<1, 1);
double xt, yt;
for (int i=0; i < nP; i++) {
xt = src.X(i) - Xt;
yt = src.Y(i) - Yt;
dst.X(i) = x11 * xt + x12 * yt;
dst.Y(i) = x21 * xt + x22 * yt;
}
}
void SimilarityTrans::setTransformByAlign(const ShapeVec &x, const ShapeVec &xp) {
int nP = x.rows / 2;
a = xp.dot(x) / x.dot(x);
b = 0;
for (int i=0; i<nP; i++)
b += x.X(i) * xp.Y(i) - x.Y(i)*xp.X(i);
b /= x.dot(x);
double xxm, xym;
xxm = x.getXMean();
xym = x.getYMean();
Xt = -a * xxm + b * xym + xp.getXMean();
Yt = -b * xxm - a * xym + xp.getYMean();
}
void ASMModel::findParamForShapeBTSM(const ShapeVec &Y, const ShapeVec &Y_old,
FitResult & fitResult, FitResult &b_old, int l)
{
//const double c[3] = {0.005, 0.005, 0.001};
const double c[3] = {0.0005, 0.0005, 0.0005};
double rho2, delta2, x2;
double p;
ShapeVec y_r, y_rpr, xFromParam, xFromY, x;
ShapeVec yt = Y_old;
yt -= Y;
rho2 = c[l] * yt.dot(yt);
SimilarityTrans curTrans = b_old.transformation;
Mat_< double > curParam, tmpFullParam, lastParam;
curParam.create(pcaPyr[l].eigenvalues.rows, 1);
for (int i=0; i<pcaPyr[l].eigenvalues.rows; i++)
if (i<b_old.params.rows)
curParam(i, 0) = b_old.params(i, 0);
else
curParam(i, 0) = 0;
//curParam = curParam.rowRange(0, pcaPyr[l].eigenvalues.rows);
int ii=0;
do{
double s = curTrans.getS();
lastParam = curParam.clone();
// Expectation Step
curTrans.backTransform(Y, y_r);
p = sigma2Pyr[l]/(sigma2Pyr[l] + rho2/(s * s));
//printf("p: %g, rho2/s2: %g, sigma2: %g\n", p, rho2/(s * s), sigma2Pyr[l]);
delta2 = 1/(1/sigma2Pyr[l] + s*s / rho2);
// printf("p: %g, rho2/s2: %g, sigma2: %g, delta2: %g\n",
// p, rho2/(s * s), sigma2Pyr[l], delta2);
this->pcaPyr[l].backProject(curParam, xFromParam);
pcaFullShape->project(y_r, tmpFullParam);
pcaFullShape->backProject(tmpFullParam, y_rpr);
x = p*y_rpr + (1-p) * xFromParam;
x2 = x.dot(x) + (x.rows - 4) * delta2;
// printf("p: %g, rho2/s2: %g, sigma2: %g, delta2: %g, x.x: %g, x2: %g\n",
// p, rho2/(s * s), sigma2Pyr[l], delta2, x.dot(x), x2);
// Maximization Step
pcaPyr[l].project(x, curParam);
for (int i=0; i<pcaPyr[l].eigenvalues.rows; i++)
curParam(i, 0) *= (pcaShape->eigenvalues.at<double>(i, 0))/
(pcaShape->eigenvalues.at<double>(i, 0)+sigma2Pyr[l]);
int nP = x.rows / 2;
curTrans.a = Y.dot(x) / x2;
curTrans.b = 0;
for (int i=0; i<nP; i++)
curTrans.b += x.X(i) * Y.Y(i) - x.Y(i)*Y.X(i);
curTrans.b /= x2;
curTrans.Xt = Y.getXMean();
curTrans.Yt = Y.getYMean();
//clampParamVec(curParam);
ii++;
} while (norm(lastParam-curParam)>1e-4 && ii<20);
fitResult.params = curParam;
fitResult.transformation = curTrans;
}
void ASMModel::resultToPointList(const FitResult& fitResult, vector< Point_<int> >& pV)
{
ShapeVec sv;
projectParamToShape(fitResult.params, sv);
sv.restoreToPointList(pV, fitResult.transformation);
}
void ASMFitResult::toPointList(vector< Point_<int> > &pV) const {
ShapeVec sv;
asmModel->projectParamToShape(params, sv);
sv.restoreToPointList(pV, transformation);
}
