void costfunc::compute_correspondences(mat &ptns, mat &sphM, uvec &matchId) {
/* ptns: reference to observed points
* sphM: reference to spheres model
* matchId:returned vector containing the matchId
*
* Match every point in the observed model to the closest sphere of
* the hand model
*
* This uses the BFMatcher provided by OpenCV
*
* ==> need to firstly convert arma::mat to cv::mat
*/
// start conversion from arma::mat --> cv::mat
fmat spheresM = conv_to<fmat>::from(sphM);
fmat ptncloud = conv_to<fmat>::from(ptns);
cv::Mat cvspheresM(spheresM.n_cols, spheresM.n_rows, CV_32F, spheresM.memptr());
cv::Mat cvptncloud(ptncloud.n_cols, ptncloud.n_rows, CV_32F, ptncloud.memptr());
// cv::mat is row-major while arma::mat is col-major
cvspheresM = cvspheresM.t();
cvptncloud = cvptncloud.t();
cv::BFMatcher matcher(cv::NORM_L2); // initialise a brute-force matcher
std::vector<cv::DMatch> matches; // initialise a container for the matches
matcher.match(cvptncloud, cvspheresM, matches); // perform matching
int cnt = ptncloud.n_rows;
matchId = zeros<uvec>(cnt);
for (int i = 0; i < cnt; i++) {
matchId.at(i) = matches[i].trainIdx;
}
}
