public bool MatchDescriptorsWithRatioTest(BFMatcher descriptorMatcher, ref Mat descriptorsEvalImage, Mat trainDescriptors, ref VectorOfDMatch matchesFilteredOut, float maxDistanceRatio)
{
if (trainDescriptors.Rows < 4)
{
return(false);
}
matchesFilteredOut.Clear();
descriptorMatcher.Add(trainDescriptors);
VectorOfVectorOfDMatch matchesKNN = new VectorOfVectorOfDMatch();
descriptorMatcher.KnnMatch(descriptorsEvalImage, matchesKNN, 2, null);
for (int matchPos = 0; matchPos < matchesKNN.Size; ++matchPos)
{
if (matchesKNN[matchPos].Size >= 2)
{
if (matchesKNN[matchPos][0].Distance <= maxDistanceRatio * matchesKNN[matchPos][1].Distance)
{
matchesFilteredOut.Push(new MDMatch[] { matchesKNN[matchPos][0] });
}
}
}
return(!(matchesFilteredOut.Size == 0));
}
public bool RefineMatchesWithHomography(VectorOfKeyPoint evalKeypoints, VectorOfKeyPoint trainKeypoints, VectorOfDMatch matches,
ref Mat homographyOut, VectorOfDMatch inliersOut, VectorOfInt inliersMaskOut,
float reprojectionThreshold, int minNumberMatchesAllowed)
{
if (matches.Size < minNumberMatchesAllowed)
{
return(false);
}
PointF[] srcPoints = new PointF[matches.Size];
PointF[] dstPoints = new PointF[matches.Size];
for (int i = 0; i < matches.Size; ++i)
{
srcPoints[i] = trainKeypoints[matches[i].TrainIdx].Point;
dstPoints[i] = evalKeypoints[matches[i].QueryIdx].Point;
}
inliersMaskOut.Clear();
inliersMaskOut = new VectorOfInt(srcPoints.Count());
//for(int i = 0; i < srcPoints.Count(); ++i)
//{
// inliersMaskOut = 0;
//}
CvInvoke.FindHomography(srcPoints, dstPoints, homographyOut, Emgu.CV.CvEnum.HomographyMethod.Ransac, reprojectionThreshold, inliersMaskOut);
for (int i = 0; i < inliersMaskOut.Size; ++i)
{
if (inliersMaskOut[i] > 0)
{
inliersOut.Push(new MDMatch[] { matches[i] });
}
}
return(inliersOut.Size >= minNumberMatchesAllowed);
}