#include "autocalib.hpp" #include "util.hpp" using namespace std; using namespace cv; void focalsFromHomography(const Mat& H, double &f0, double &f1, bool &f0_ok, bool &f1_ok) { CV_Assert(H.type() == CV_64F && H.size() == Size(3, 3)); const double* h = reinterpret_cast<const double*>(H.data); double d1, d2; // Denominators double v1, v2; // Focal squares value candidates f1_ok = true; d1 = h[6] * h[7]; d2 = (h[7] - h[6]) * (h[7] + h[6]); v1 = -(h[0] * h[1] + h[3] * h[4]) / d1; v2 = (h[0] * h[0] + h[3] * h[3] - h[1] * h[1] - h[4] * h[4]) / d2; if (v1 < v2) swap(v1, v2); if (v1 > 0 && v2 > 0) f1 = sqrt(abs(d1) > abs(d2) ? v1 : v2); else if (v1 > 0) f1 = sqrt(v1); else f1_ok = false; f0_ok = true; d1 = h[0] * h[3] + h[1] * h[4]; d2 = h[0] * h[0] + h[1] * h[1] - h[3] * h[3] - h[4] * h[4]; v1 = -h[2] * h[5] / d1; v2 = (h[5] * h[5] - h[2] * h[2]) / d2; if (v1 < v2) swap(v1, v2); if (v1 > 0 && v2 > 0) f0 = sqrt(abs(d1) > abs(d2) ? v1 : v2); else if (v1 > 0) f0 = sqrt(v1); else f0_ok = false; } double estimateFocal(const vector<ImageFeatures> &features, const vector<MatchesInfo> &pairwise_matches) { const int num_images = static_cast<int>(features.size()); vector<double> focals; for (int src_idx = 0; src_idx < num_images; ++src_idx) { for (int dst_idx = 0; dst_idx < num_images; ++dst_idx) { const MatchesInfo &m = pairwise_matches[src_idx*num_images + dst_idx]; if (m.H.empty()) continue; double f0, f1; bool f0ok, f1ok; focalsFromHomography(m.H, f0, f1, f0ok, f1ok); if (f0ok && f1ok) focals.push_back(sqrt(f0*f1)); } } if (static_cast<int>(focals.size()) >= 2 * (num_images - 1)) { nth_element(focals.begin(), focals.end(), focals.begin() + focals.size()/2); return focals[focals.size()/2]; } LOGLN("Can't estimate focal length, will use naive approach"); double focals_sum = 0; for (int i = 0; i < num_images; ++i) focals_sum += features[i].img_size.width + features[i].img_size.height; return focals_sum / num_images; }