Although the documentation for the find_optimal_parameters function of the find_optimal_parameters library was really insufficient, there is a unit test that you can find on github that shows how to use this function.
I saw another question that you asked, and it seems that the solution was something else than in this question. However, here is an example of how to use the library (this is the first time I hear about it) to calculate what you need or something very close to this. You will probably need to change the DistanceQuality () function (replacing the existing loop with two nested ones), and I will let you do it yourself.
Please note that all the contents of the code are hard-coded, error handling is not performed, and testing is performed directly in the main () function. There is a lot of work to be done, although you can find code that works for illustration.
Here we go:
#include <iostream> #include <dlib/optimization.h> #include <dlib/optimization/find_optimal_parameters.h> using namespace dlib; typedef matrix<double, 3, 1> MyPoint; std::vector<MyPoint> points; std::vector<double> distances; double MyDistance(MyPoint point1, MyPoint point2) { double sum = 0; for (int i = 0; i < 3; i++) { sum += (point1(i, 0) - point2(i, 0)) * (point1(i, 0) - point2(i, 0)); } return sqrt(sum); } double DistanceQuality(const matrix<double, 3, 3>& H) { double sum = 0; for (int i = 0; i < points.size() - 1; i++) { auto proj1 = H*points[i]; auto proj2 = H*points[i+1]; sum += abs(MyDistance(proj1, proj2) - distances[i]); } return sum; } matrix<double, 3, 3> VecToMatrix(matrix<double, 0, 1> vec) { matrix<double, 3, 3> matrix; for (int i = 0; i < 9; i++) { matrix(i / 3, i % 3) = vec(i); } return matrix; } double test_function(matrix<double, 0, 1> H) { matrix<double, 3, 3> newH = VecToMatrix(H); auto result = DistanceQuality(newH); return result; } int main() { matrix<double, 3, 1> p1; matrix<double, 3, 1> p2; matrix<double, 3, 1> p3; p1 = { 1, 1, 1 }; p2 = { 2, 2, 3 }; p3 = { 3, 1.6, 7}; points.push_back(p1); points.push_back(p2); points.push_back(p3); double d1 = 2.44949; double d2 = 4.142463; distances.push_back(d1); distances.push_back(d2); matrix<double, 0, 1> H; H = { 3, 1, 1, 1, 1, 6, 1, 4, 1 }; matrix<double, 0, 1> H_min; matrix<double, 0, 1> H_max; H_min = { 0.5, 0.6, 0.5, 0.5, 0.7, 0.5, 0.8, 0.3, 0.5, }; H_max = { 10, 10, 10, 10, 10, 10, 10, 10, 10, }; dlib::find_optimal_parameters(4, 0.001, 1000, H, H_min, H_max, test_function); std::cout << "new H: " << std::endl << VecToMatrix(H) << std::endl; return 0; }
I hope you can adapt the parameters for a specific case.