After reading the description of the opencv's following function:
recallPrecisionCurve = cv.computeRecallPrecisionCurve(matches1to2, correctMatches1to2Mask)
I have 2 important queries.
1) How can we get correctMatches1to2Mask (input for the above function)? If it is to be found using outlier rejection through RANSAC, then what about the False Negatives (the feature points which were detected in both images and could be matched, but they were neglected by the feature descriptor under test) ? False Negatives are used in the formula of Recall: Recall = True Positives / (False Negatives + True Positives)
2) The output of this function is a Nx2 matrix. First column of this output matrix gives Recall values or Precision values?