Homography, inliers / Emgu CV / SURF in C #

Question

How can I get inliers / outliers of matching kyepoints using homography or some other method in C #?

I am working on a SURF example provided at http://www.emgu.com/wiki/index.php/SURF_feature_detector_in_CSharp .

I got a match. The code uses HomographyMatrix (homography). I want to separate levels and emissions.

In C ++:

bgroup({findFundamentalMat}) int cvFindFundamentalMat(const CvMat* points1, const CvMat* points2, CvMat* fundamentalMatrix, int method=CV_FM_RANSAC, double param1=1., double param2=0.99, CvMat* status=NULL) 

returns values. Can I see similar code also in C #.

Again, I just need to highlight the emissions / molt.

Answer 1

Your question is not so clear, because if you use homgus emgucv computation, it is evaluated using the CameraCalibration.FindHomography() function using RANSAC if there are more than 10 match pairs. I am working on these topics for my dissertation, so I will publish some appropriate code that should fully answer you and serve others.

 result = MatchingRefinement.VoteForSizeAndOrientation(result, 1.5, 20); homography = MatchingRefinement. GetHomographyMatrixFromMatchedFeatures(result, HomographyDirection.DIRECT, HOMOGRAPHY_METHOD.LMEDS); inverseHomography = MatchingRefinement.GetHomographyMatrixFromMatchedFeatures( result, HomographyDirection.INVERSE, HOMOGRAPHY_METHOD.LMEDS); PointF[] pts1 = new PointF[result.Length]; PointF[] pts1_t = new PointF[result.Length]; PointF[] pts2 = new PointF[result.Length]; for (int i = 0; i < result.Length; i++) { pts1[i] = result[i].ObservedFeature.KeyPoint.Point; pts1_t[i] = result[i].ObservedFeature.KeyPoint.Point; pts2[i] = result[i].SimilarFeatures[0].Feature.KeyPoint.Point; } // Project model features according to homography homography.ProjectPoints(pts1_t); Image<Bgr, Byte> finalCorrespondance = inputImage.Copy(); matchedInliersFeatures = new List<MatchedImageFeature>(); for (int i1 = 0; i1 < pts1_t.Length; i1++) { if (Math.Sqrt(Math.Pow(pts2[i1].X - pts1_t[i1].X, 2d) + Math.Pow(pts2[i1].Y - pts1_t[i1].Y, 2d)) <4d) // Inlier { PointF p_t = pts1_t[i1]; PointF p = pts1[i1]; finalCorrespondance.Draw(new CircleF(p, 2f), new Bgr(Color.Yellow), 2); finalCorrespondance.Draw(new CircleF(p_t, 2f), new Bgr(Color.Black), 2); finalCorrespondance.Draw(new LineSegment2DF(p, p_t), new Bgr(Color.Blue), 1); MatchedImageFeature feature = new MatchedImageFeature(); feature.SimilarFeatures = new SimilarFeature[] { result[i1].SimilarFeatures[0] }; feature.ObservedFeature = result[i1].ObservedFeature; matchedInliersFeatures.Add(feature); } } List<ImageFeature> inliers = new List<ImageFeature>(); foreach (MatchedImageFeature match in matchedInliersFeatures) { inliers.Add(match.ObservedFeature); inliers.Add(match.SimilarFeatures[0].Feature); } 

Answer 2

If you want to split sheets / emissions and you already have matches, try the following:

 //**RANSAC OUTLIER REMOVAL **// Mat status; vector<Point2f> trainMatches; vector<Point2f> queryMatches; vector<DMatch> inliers; for( int i = 0; i < goodmatches.size(); i++ ) { //-- Get the keypoints from the good matches trainMatches.push_back( cv::Point2f(keypointsB[ goodmatches[i].trainIdx ].pt.x/640.0f, keypointsB[ goodmatches[i].trainIdx ].pt.y/480.0f) ); queryMatches.push_back( cv::Point2f(keypointsA[ goodmatches[i].queryIdx ].pt.x/640.0f, keypointsA[ goodmatches[i].queryIdx ].pt.y/480.0f) ); } Mat _homography; Mat h = cv::findHomography(trainMatches,queryMatches,CV_RANSAC,0.005, status); for(size_t i = 0; i < queryMatches.size(); i++) { if(status.at<char>(i) != 0) { inliers.push_back(goodmatches[i]); } } 

Note that I normalized the points, so the homography score is more reliable.

Answer 3

The cvFindFundamentalMat signature in C # will look like this:

 int cvFindFundamentalMat(CvMat points1, CvMat points2, CvMat fundamentalMatrix, CV_FM method, double param1, double param2, CvMat status); 

The default setting was introduced in C # 4.0. I assume that Emgu CV does not support .NET 4.0 yet (correct me if I am mistaken), so one could do an overload providing default values:

 int cvFindFundamentalMat(CvMat points1, CvMat points2, CvMat fundamentalMatrix) { return cvFindFundamentalMat(points1, points2, fundamentalMatrix, CV_FM.CV_FM_RANSAC, 1.0, 0.99, null); } 

Note: as commentators noted, it’s hard to be sure what you are asking. Here, I only guessed that some of your questions were about how the presented C ++ code would look in C #.