/// <summary>
/// Create a matched feature structure.
/// </summary>
/// <param name="observedFeature">The feature from the observed image</param>
/// <param name="modelFeatures">The matched feature from the model</param>
/// <param name="dist">The distances between the feature from the observerd image and the matched feature from the model image</param>
public MatchedSURFFeature(SURFFeature observedFeature, SURFFeature[] modelFeatures, double[] dist)
{
ObservedFeature = observedFeature;
_similarFeatures = new SimilarFeature[modelFeatures.Length];
for (int i = 0; i < modelFeatures.Length; i++)
{
_similarFeatures[i] = new SimilarFeature(dist[i], modelFeatures[i]);
}
}
/// <summary>
/// Create a matched feature structure.
/// </summary>
/// <param name="observedFeature">The feature from the observed image</param>
/// <param name="modelFeatures">The matched feature from the model</param>
/// <param name="dist">The distances between the feature from the observerd image and the matched feature from the model image</param>
public MatchedImageFeature(ImageFeature <TDescriptor> observedFeature, ImageFeature <TDescriptor>[] modelFeatures, double[] dist)
{
ObservedFeature = observedFeature;
_similarFeatures = new SimilarFeature[modelFeatures.Length];
for (int i = 0; i < modelFeatures.Length; i++)
{
_similarFeatures[i] = new SimilarFeature(dist[i], modelFeatures[i]);
}
}
/// <summary>
/// Create a matched feature structure.
/// </summary>
/// <param name="observedFeature">The feature from the observed image</param>
/// <param name="modelFeatures">The matched feature from the model</param>
/// <param name="dist">The distances between the feature from the observerd image and the matched feature from the model image</param>
public MatchedSURFFeature(SURFFeature observedFeature, SURFFeature[] modelFeatures, double[] dist)
{
ObservedFeature = observedFeature;
_similarFeatures = new SimilarFeature[modelFeatures.Length];
for (int i = 0; i < modelFeatures.Length; i++)
_similarFeatures[i] = new SimilarFeature(dist[i], modelFeatures[i]);
}
/// <summary>
/// Convert the raw keypoints and descriptors to array of managed structure.
/// </summary>
/// <param name="modelKeyPointVec">The model keypoint vector</param>
/// <param name="modelDescriptorMat">The mode descriptor vector</param>
/// <param name="observedKeyPointVec">The observerd keypoint vector</param>
/// <param name="observedDescriptorMat">The observed descriptor vector</param>
/// <param name="indices">The indices matrix</param>
/// <param name="dists">The distances matrix</param>
/// <param name="mask">The mask</param>
/// <returns>The managed MatchedImageFeature array</returns>
public static MatchedImageFeature[] ConvertToMatchedImageFeature(
VectorOfKeyPoint modelKeyPointVec, Matrix <TDescriptor> modelDescriptorMat,
VectorOfKeyPoint observedKeyPointVec, Matrix <TDescriptor> observedDescriptorMat,
Matrix <int> indices, Matrix <float> dists, Matrix <Byte> mask)
{
MKeyPoint[] modelKeyPoints = modelKeyPointVec.ToArray();
MKeyPoint[] observedKeyPoints = observedKeyPointVec.ToArray();
int resultLength = (mask == null) ? observedKeyPoints.Length : CvInvoke.cvCountNonZero(mask);
MatchedImageFeature[] result = new MatchedImageFeature[resultLength];
MCvMat modelMat = (MCvMat)Marshal.PtrToStructure(modelDescriptorMat.Ptr, typeof(MCvMat));
long modelPtr = modelMat.data.ToInt64();
int modelStep = modelMat.step;
MCvMat observedMat = (MCvMat)Marshal.PtrToStructure(observedDescriptorMat.Ptr, typeof(MCvMat));
long observedPtr = observedMat.data.ToInt64();
int observedStep = observedMat.step;
int descriptorLength = modelMat.cols;
int descriptorSizeInByte = descriptorLength * Marshal.SizeOf(typeof(TDescriptor));
int k = dists.Cols;
TDescriptor[] tmp = new TDescriptor[descriptorLength];
GCHandle handle = GCHandle.Alloc(tmp, GCHandleType.Pinned);
IntPtr address = handle.AddrOfPinnedObject();
int resultIdx = 0;
for (int i = 0; i < observedKeyPoints.Length; i++)
{
if (mask != null && mask.Data[i, 0] == 0)
{
continue;
}
SimilarFeature[] features = new SimilarFeature[k];
for (int j = 0; j < k; j++)
{
features[j].Distance = dists.Data[i, j];
ImageFeature <TDescriptor> imgFeature = new ImageFeature <TDescriptor>();
int idx = indices.Data[i, j];
if (idx == -1)
{
Array.Resize(ref features, j);
break;
}
imgFeature.KeyPoint = modelKeyPoints[idx];
imgFeature.Descriptor = new TDescriptor[descriptorLength];
Emgu.Util.Toolbox.memcpy(address, new IntPtr(modelPtr + modelStep * idx), descriptorSizeInByte);
tmp.CopyTo(imgFeature.Descriptor, 0);
features[j].Feature = imgFeature;
}
result[resultIdx].SimilarFeatures = features;
ImageFeature <TDescriptor> observedFeature = new ImageFeature <TDescriptor>();
observedFeature.KeyPoint = observedKeyPoints[i];
observedFeature.Descriptor = new TDescriptor[descriptorLength];
Emgu.Util.Toolbox.memcpy(address, new IntPtr(observedPtr + observedStep * i), descriptorSizeInByte);
tmp.CopyTo(observedFeature.Descriptor, 0);
result[resultIdx].ObservedFeature = observedFeature;
resultIdx++;
}
handle.Free();
return(result);
}
