Gaussian3D build_gaussian(std::string image_names[], int length, double **pixels)
// Builds the initial hand and background gaussians from files.
{
int total_averaged_rgbs = 0;
for (int index =0; index<length; index++) {
std::string image = image_names[index];
cv::Mat img;
img = cv::imread(image);
int count = 0;
double *sum = new double[3];
sum[0] = 0.0;
sum[1] = 0.0;
sum[2] = 0.0;
for (int i=0; i<img.rows; i++) {
for (int j=0; j<img.cols; j++) {
cv::Vec3b bgrPixel = img.at<cv::Vec3b>(i,j);
sum[0] += (double)bgrPixel[0]/255;
sum[1] += (double)bgrPixel[1]/255;
sum[2] += (double)bgrPixel[2]/255;
count++;
}
}
sum[0] = sum[0] / count;
sum[1] = sum[1] / count;
sum[2] = sum[2] / count;
pixels[index] = sum;
total_averaged_rgbs++;
}
Gaussian3D result = Gaussian3D(pixels, total_averaged_rgbs);
return result;
}
Gaussian3D get_gaussian_from_covariance(const IMP_Eigen::Matrix3d &covar,
const Vector3D ¢er) {
Rotation3D rot;
Vector3D radii;
// get eigen decomposition and sort by eigen vector
IMP_Eigen::EigenSolver<IMP_Eigen::Matrix3d> es(covar);
IMP_Eigen::Matrix3d evecs = es.eigenvectors().real();
IMP_Eigen::Vector3d evals = es.eigenvalues().real();
// fill in sorted stuff
for (int i = 0; i < 3; i++) {
radii[i] = evals[i];
}
// reflect if necessary
double det = evecs.determinant();
// std::cout<<"Determinant is "<<det<<std::endl;
if (det < 0) {
IMP_Eigen::Matrix3d reflect = IMP_Eigen::Vector3d(1, 1, -1).asDiagonal();
evecs = evecs * reflect;
}
// create rotation matrix and return
IMP_Eigen::Quaterniond eq(evecs);
rot = Rotation3D(eq.w(), eq.x(), eq.y(), eq.z());
return Gaussian3D(ReferenceFrame3D(Transformation3D(rot, center)), radii);
}