public static List <ImageSearchResult> SearchImageForObjects(WorldObject modelObject, string imageToSearch)
{
int k = 2;
double uniquenessThreshold = 0.8;
double hessianThresh = 300;
int nonZeroThreshold = 10;
ObjectFeatures targetImageFeatures = DetectFeatures_Brisk(imageToSearch);
Mat mask;
List <ImageSearchResult> searchResults = new List <ImageSearchResult>();
foreach (ObjectView view in modelObject.Views)
{
if (view == null)
{
continue;
}
VectorOfVectorOfDMatch matches = new VectorOfVectorOfDMatch();
BFMatcher matcher = new BFMatcher(DistanceType.L2);
matcher.Add(view.Features.Descriptors);
matcher.KnnMatch(targetImageFeatures.Descriptors, matches, 2, null);
mask = new Mat(matches.Size, 1, DepthType.Cv8U, 1);
mask.SetTo(new MCvScalar(255));
Features2DToolbox.VoteForUniqueness(matches, uniquenessThreshold, mask);
int nonZeroCount = CvInvoke.CountNonZero(mask);
if (nonZeroCount >= nonZeroThreshold)
{
nonZeroCount = Features2DToolbox.VoteForSizeAndOrientation(view.Features.KeyPoints,
targetImageFeatures.KeyPoints, matches, mask, 1.5, 20);
if (nonZeroCount >= nonZeroThreshold)
{
Mat homography = Features2DToolbox.GetHomographyMatrixFromMatchedFeatures(view.Features.KeyPoints,
targetImageFeatures.KeyPoints, matches, mask, 2);
searchResults.Add(new ImageSearchResult(view, homography, matches, targetImageFeatures, mask));
}
}
}
return(searchResults);
}
public ObjectView(Perspective perspective, string imagePath)
{
this._imagePerspective = perspective;
this._imagePath = imagePath;
this.Features = FeatureDetector.DetectFeatures_Brisk(imagePath);
}
public ImageSearchResult(ObjectView view, Mat homography, VectorOfVectorOfDMatch matches, ObjectFeatures observedFeatures, Mat mask)
{
this.MatchingView = view;
this.Homography = homography;
this.Matches = matches;
this.ObservedFeatures = observedFeatures;
this.Mask = mask;
}